Search Results for author: Jie Zhang

Found 414 papers, 157 papers with code

Membership Inference Attacks on Sequence Models

no code implementations5 Jun 2025 Lorenzo Rossi, Michael Aerni, Jie Zhang, Florian Tramèr

Sequence models, such as Large Language Models (LLMs) and autoregressive image generators, have a tendency to memorize and inadvertently leak sensitive information.

Inference Attack Membership Inference Attack +1

A Composite Predictive-Generative Approach to Monaural Universal Speech Enhancement

no code implementations30 May 2025 Jie Zhang, Haoyin Yan, Xiaofei Li

It is promising to design a single model that can suppress various distortions and improve speech quality, i. e., universal speech enhancement (USE).

Denoising Speech Enhancement

Light as Deception: GPT-driven Natural Relighting Against Vision-Language Pre-training Models

no code implementations30 May 2025 Ying Yang, Jie Zhang, Xiao Lv, Di Lin, Tao Xiang, Qing Guo

To address this, we propose \textbf{LightD}, a novel framework that generates natural adversarial samples for VLP models via semantically guided relighting.

Image Captioning Question Answering +1

Generalizable Heuristic Generation Through Large Language Models with Meta-Optimization

no code implementations27 May 2025 Yiding Shi, Jianan Zhou, Wen Song, Jieyi Bi, Yaoxin Wu, Jie Zhang

Heuristic design with large language models (LLMs) has emerged as a promising approach for tackling combinatorial optimization problems (COPs).

Combinatorial Optimization Meta-Learning

Reinforcement Speculative Decoding for Fast Ranking

no code implementations23 May 2025 Yingpeng Du, Tianjun Wei, Zhu Sun, Jie Zhang

Although speculative decoding (SD) methods can be a remedy with verification at different positions, they face challenges in ranking systems due to their left-to-right decoding paradigm.

Information Retrieval Recommendation Systems +1

A Unified Gradient-based Framework for Task-agnostic Continual Learning-Unlearning

no code implementations21 May 2025 Zhehao Huang, Xinwen Cheng, Jie Zhang, JingHao Zheng, Haoran Wang, Zhengbao He, Tao Li, Xiaolin Huang

Recent advancements in deep models have highlighted the need for intelligent systems that combine continual learning (CL) for knowledge acquisition with machine unlearning (MU) for data removal, forming the Continual Learning-Unlearning (CLU) paradigm.

Continual Learning Incremental Learning +1

Table-R1: Region-based Reinforcement Learning for Table Understanding

no code implementations18 May 2025 Zhenhe Wu, Jian Yang, Jiaheng Liu, Xianjie Wu, Changzai Pan, Jie Zhang, Yu Zhao, Shuangyong Song, Yongxiang Li, Zhoujun Li

Tables present unique challenges for language models due to their structured row-column interactions, necessitating specialized approaches for effective comprehension.

Question Answering reinforcement-learning +1

RealMath: A Continuous Benchmark for Evaluating Language Models on Research-Level Mathematics

1 code implementation18 May 2025 Jie Zhang, Cezara Petrui, Kristina Nikolić, Florian Tramèr

Existing benchmarks for evaluating mathematical reasoning in large language models (LLMs) rely primarily on competition problems, formal proofs, or artificially challenging questions -- failing to capture the nature of mathematics encountered in actual research environments.

Mathematical Reasoning

SubGCache: Accelerating Graph-based RAG with Subgraph-level KV Cache

no code implementations16 May 2025 Qiuyu Zhu, Liang Zhang, Qianxiong Xu, Cheng Long, Jie Zhang

Graph-based retrieval-augmented generation (RAG) enables large language models (LLMs) to incorporate structured knowledge via graph retrieval as contextual input, enhancing more accurate and context-aware reasoning.

RAG Retrieval +1

BMMDetect: A Multimodal Deep Learning Framework for Comprehensive Biomedical Misconduct Detection

no code implementations9 May 2025 Yize Zhou, Jie Zhang, Meijie Wang, Lun Yu

Academic misconduct detection in biomedical research remains challenging due to algorithmic narrowness in existing methods and fragmented analytical pipelines.

Articles Feature Importance +1

Clustering with Communication: A Variational Framework for Single Cell Representation Learning

no code implementations8 May 2025 Cong Qi, Yeqing Chen, Jie Zhang, Wei Zhi

Single-cell RNA sequencing (scRNA-seq) has revealed complex cellular heterogeneity, but recent studies emphasize that understanding biological function also requires modeling cell-cell communication (CCC), the signaling interactions mediated by ligand-receptor pairs that coordinate cellular behavior.

Representation Learning

Holmes: Automated Fact Check with Large Language Models

no code implementations6 May 2025 Haoran Ou, Gelei Deng, Xingshuo Han, Jie Zhang, Xinlei He, Han Qiu, Shangwei Guo, Tianwei Zhang

The rise of Internet connectivity has accelerated the spread of disinformation, threatening societal trust, decision-making, and national security.

Fact Checking Retrieval

Enhancing New-item Fairness in Dynamic Recommender Systems

1 code implementation30 Apr 2025 Huizhong Guo, Zhu Sun, Dongxia Wang, Tianjun Wei, Jinfeng Li, Jie Zhang

In addition, FairAgent introduces a novel reward mechanism for recommendation tailored to the characteristics of DRSs, which consists of three components: 1) a new-item exploration reward to promote the exposure of dynamically introduced new-items, 2) a fairness reward to adapt to users' personalized fairness requirements for new-items, and 3) an accuracy reward which leverages users' dynamic feedback to enhance recommendation accuracy.

Fairness Knowledge Distillation +2

Inception: Jailbreak the Memory Mechanism of Text-to-Image Generation Systems

no code implementations29 Apr 2025 Shiqian Zhao, Jiayang Liu, Yiming Li, Runyi Hu, Xiaojun Jia, Wenshu Fan, Xinfeng Li, Jie Zhang, Wei Dong, Tianwei Zhang, Luu Anh Tuan

Different from previous attacks that fuse the unsafe target prompt into one ultimate adversarial prompt, which can be easily detected or may generate non-unsafe images due to under- or over-optimization, we propose Inception, the first multi-turn jailbreak attack against the memory mechanism in real-world text-to-image generation systems.

Text to Image Generation Text-to-Image Generation

Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models

1 code implementation29 Apr 2025 Zhongqi Wang, Jie Zhang, Shiguang Shan, Xilin Chen

To quantify these dynamic anomalies, we first introduce DAA-I, which treats the tokens' attention maps as spatially independent and measures dynamic feature using the Frobenius norm.

Backdoor Attack

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

no code implementations22 Apr 2025 Kun Wang, Guibin Zhang, Zhenhong Zhou, Jiahao Wu, Miao Yu, Shiqian Zhao, Chenlong Yin, Jinhu Fu, Yibo Yan, Hanjun Luo, Liang Lin, Zhihao Xu, Haolang Lu, Xinye Cao, Xinyun Zhou, Weifei Jin, Fanci Meng, Shicheng Xu, Junyuan Mao, Yu Wang, Hao Wu, Minghe Wang, Fan Zhang, Junfeng Fang, Wenjie Qu, Yue Liu, Chengwei Liu, Yifan Zhang, Qiankun Li, Chongye Guo, Yalan Qin, Zhaoxin Fan, Kai Wang, Yi Ding, Donghai Hong, Jiaming Ji, Yingxin Lai, Zitong Yu, Xinfeng Li, Yifan Jiang, Yanhui Li, Xinyu Deng, Junlin Wu, Dongxia Wang, Yihao Huang, Yufei Guo, Jen-tse Huang, Qiufeng Wang, Xiaolong Jin, Wenxuan Wang, Dongrui Liu, Yanwei Yue, Wenke Huang, Guancheng Wan, Heng Chang, Tianlin Li, Yi Yu, Chenghao Li, Jiawei Li, Lei Bai, Jie Zhang, Qing Guo, Jingyi Wang, Tianlong Chen, Joey Tianyi Zhou, Xiaojun Jia, Weisong Sun, Cong Wu, Jing Chen, Xuming Hu, Yiming Li, Xiao Wang, Ningyu Zhang, Luu Anh Tuan, Guowen Xu, Jiaheng Zhang, Tianwei Zhang, Xingjun Ma, Jindong Gu, Liang Pang, Xiang Wang, Bo An, Jun Sun, Mohit Bansal, Shirui Pan, Lingjuan Lyu, Yuval Elovici, Bhavya Kailkhura, Yaodong Yang, Hongwei Li, Wenyuan Xu, Yizhou Sun, Wei Wang, Qing Li, Ke Tang, Yu-Gang Jiang, Felix Juefei-Xu, Hui Xiong, XiaoFeng Wang, DaCheng Tao, Philip S. Yu, Qingsong Wen, Yang Liu

Currently, existing surveys on LLM safety primarily focus on specific stages of the LLM lifecycle, e. g., deployment phase or fine-tuning phase, lacking a comprehensive understanding of the entire "lifechain" of LLMs.

Model Editing

MetaMolGen: A Neural Graph Motif Generation Model for De Novo Molecular Design

no code implementations22 Apr 2025 Zimo Yan, Jie Zhang, Zheng Xie, Chang Liu, Yizhen Liu, Yiping Song

Molecular generation plays an important role in drug discovery and materials science, especially in data-scarce scenarios where traditional generative models often struggle to achieve satisfactory conditional generalization.

Drug Discovery Meta-Learning +1

Mask Image Watermarking

1 code implementation17 Apr 2025 Runyi Hu, Jie Zhang, Shiqian Zhao, Nils Lukas, Jiwei Li, Qing Guo, Han Qiu, Tianwei Zhang

MaskMark has two variants: (1) MaskMark-D, which supports global watermark embedding, watermark localization, and local watermark extraction for applications such as tamper detection; (2) MaskMark-ED, which focuses on local watermark embedding and extraction, offering enhanced robustness in small regions to support fine-grined image protection.

Computational Efficiency Decoder

The Jailbreak Tax: How Useful are Your Jailbreak Outputs?

1 code implementation14 Apr 2025 Kristina Nikolić, Luze Sun, Jie Zhang, Florian Tramèr

For example, while all jailbreaks we tested bypass guardrails in models aligned to refuse to answer math, this comes at the expense of a drop of up to 92% in accuracy.

Math

Ray-Based Characterization of the AMPLE Model from 0.85 to 5 GHz

no code implementations12 Apr 2025 Lingyou Zhou, Xin Dong, Kehai Qiu, Gang Yu, Jie Zhang, Jiliang Zhang

In this paper, we characterize the adaptive multiple path loss exponent (AMPLE) radio propagation model under urban macrocell (UMa) and urban microcell (UMi) scenarios from 0. 85-5 GHz using Ranplan Professional.

Prediction

Distilling Textual Priors from LLM to Efficient Image Fusion

1 code implementation9 Apr 2025 Ran Zhang, Xuanhua He, Ke Cao, Liu Liu, Li Zhang, Man Zhou, Jie Zhang

The distilled network, requiring only 10% of the parameters and inference time of the teacher network, retains 90% of its performance and outperforms existing SOTA methods.

Computational Efficiency

Clean Image May be Dangerous: Data Poisoning Attacks Against Deep Hashing

no code implementations27 Mar 2025 Shuai Li, Jie Zhang, Yuang Qi, Kejiang Chen, Tianwei Zhang, Weiming Zhang, Nenghai Yu

It is worth noting that these attacks typically involve altering the query images, which is not a practical concern in real-world scenarios.

Data Poisoning Deep Hashing +1

Surgical Action Planning with Large Language Models

no code implementations24 Mar 2025 Mengya Xu, Zhongzhen Huang, Jie Zhang, Xiaofan Zhang, Qi Dou

Large Language Models (LLMs) show promise in understanding surgical video content but remain underexplored for predictive decision-making in SAP, as they focus mainly on retrospective analysis.

Decision Making

Towards Invisible Backdoor Attack on Text-to-Image Diffusion Model

1 code implementation22 Mar 2025 Jie Zhang, Zhongqi Wang, Shiguang Shan, Xilin Chen

Backdoor attacks targeting text-to-image diffusion models have advanced rapidly, enabling attackers to implant malicious triggers into these models to manipulate their outputs.

Backdoor Attack

Exploiting Vulnerabilities in Speech Translation Systems through Targeted Adversarial Attacks

no code implementations2 Mar 2025 Chang Liu, Haolin Wu, Xi Yang, Kui Zhang, Cong Wu, Weiming Zhang, Nenghai Yu, Tianwei Zhang, Qing Guo, Jie Zhang

As speech translation (ST) systems become increasingly prevalent, understanding their vulnerabilities is crucial for ensuring robust and reliable communication.

Translation

RFWNet: A Lightweight Remote Sensing Object Detector Integrating Multi-Scale Receptive Fields and Foreground Focus Mechanism

no code implementations1 Mar 2025 Yujie Lei, Wenjie Sun, Sen Jia, Qingquan Li, Jie Zhang

Challenges in remote sensing object detection (RSOD), such as high inter-class similarity, imbalanced foreground-background distribution, and the small size of objects in remote sensing images significantly hinder detection accuracy.

object-detection Object Detection

RelaCtrl: Relevance-Guided Efficient Control for Diffusion Transformers

no code implementations20 Feb 2025 Ke Cao, Jing Wang, Ao Ma, Jiasong Feng, Zhanjie Zhang, Xuanhua He, Shanyuan Liu, Bo Cheng, Dawei Leng, Yuhui Yin, Jie Zhang

The Diffusion Transformer plays a pivotal role in advancing text-to-image and text-to-video generation, owing primarily to its inherent scalability.

Text-to-Video Generation Video Generation

Does Training with Synthetic Data Truly Protect Privacy?

1 code implementation18 Feb 2025 Yunpeng Zhao, Jie Zhang

As synthetic data becomes increasingly popular in machine learning tasks, numerous methods--without formal differential privacy guarantees--use synthetic data for training.

Data-free Knowledge Distillation Dataset Distillation

Related Knowledge Perturbation Matters: Rethinking Multiple Pieces of Knowledge Editing in Same-Subject

1 code implementation8 Feb 2025 Zenghao Duan, Wenbin Duan, Zhiyi Yin, Yinghan Shen, Shaoling Jing, Jie Zhang, HuaWei Shen, Xueqi Cheng

Knowledge editing has become a promising approach for efficiently and precisely updating knowledge embedded in large language models (LLMs).

knowledge editing

Adversarial ML Problems Are Getting Harder to Solve and to Evaluate

no code implementations4 Feb 2025 Javier Rando, Jie Zhang, Nicholas Carlini, Florian Tramèr

In the past decade, considerable research effort has been devoted to securing machine learning (ML) models that operate in adversarial settings.

Position

Converting Transformers into DGNNs Form

1 code implementation1 Feb 2025 Jie Zhang, Kuan-Chieh Wang, Bo-Wei Chiu, Min-Te Sun

Recent advances in deep learning have established Transformer architectures as the predominant modeling paradigm.

Computational Efficiency Document Classification +2

VideoShield: Regulating Diffusion-based Video Generation Models via Watermarking

1 code implementation24 Jan 2025 Runyi Hu, Jie Zhang, Yiming Li, Jiwei Li, Qing Guo, Han Qiu, Tianwei Zhang

Artificial Intelligence Generated Content (AIGC) has advanced significantly, particularly with the development of video generation models such as text-to-video (T2V) models and image-to-video (I2V) models.

Denoising Image Generation +1

Pre-train and Fine-tune: Recommenders as Large Models

no code implementations24 Jan 2025 Zhenhao Jiang, Chenghao Chen, Hao Feng, Yu Yang, Jin Liu, Jie Zhang, Jia Jia, Ning Hu

We first propose the theory of the information bottleneck for fine-tuning and present an explanation for the fine-tuning technique in recommenders.

Recommendation Systems

The First Indoor Pathloss Radio Map Prediction Challenge

no code implementations23 Jan 2025 Stefanos Bakirtzis, Çağkan Yapar, Kehai Qiu, Ian Wassell, Jie Zhang

To encourage further research and to facilitate fair comparisons in the development of deep learning-based radio propagation models, in the less explored case of directional radio signal emissions in indoor propagation environments, we have launched the ICASSP 2025 First Indoor Pathloss Radio Map Prediction Challenge.

Prediction

Energy Consumption Reduction for UAV Trajectory Training : A Transfer Learning Approach

no code implementations20 Jan 2025 Chenrui Sun, Swarna Bindu Chetty, Gianluca Fontanesi, Jie Zhang, Amirhossein Mohajerzadeh, David Grace, Hamed Ahmadi

The advent of 6G technology demands flexible, scalable wireless architectures to support ultra-low latency, high connectivity, and high device density.

Transfer Learning

Normalize Then Propagate: Efficient Homophilous Regularization for Few-shot Semi-Supervised Node Classification

1 code implementation15 Jan 2025 Baoming Zhang, Mingcai Chen, Jianqing Song, Shuangjie Li, Jie Zhang, Chongjun Wang

In this paper, we first analyze the restrictions of GNNs generalization from the perspective of supervision signals in the context of few-shot semi-supervised node classification.

Node Classification

Three-dimensional attention Transformer for state evaluation in real-time strategy games

no code implementations7 Jan 2025 Yanqing Ye, Weilong Yang, Kai Qiu, Jie Zhang

Situation assessment in Real-Time Strategy (RTS) games is crucial for understanding decision-making in complex adversarial environments.

Decision Making Real-Time Strategy Games

Online Reinforcement Learning-Based Dynamic Adaptive Evaluation Function for Real-Time Strategy Tasks

no code implementations7 Jan 2025 Weilong Yang, Jie Zhang, Xunyun Liu, Yanqing Ye

Building on traditional static evaluation functions, the method employs gradient descent in online reinforcement learning to update weights dynamically, incorporating weight decay techniques to ensure stability.

reinforcement-learning Reinforcement Learning

Face Forgery Video Detection via Temporal Forgery Cue Unraveling

no code implementations CVPR 2025 Zonghui Guo, Yingjie Liu, Jie Zhang, Haiyong Zheng, Shiguang Shan

Then, we devise a future guide module to unravel inconsistency cues by iteratively aggregating historical anomaly cues and gradually propagating them into future frames.

Video-Bench: Human-Aligned Video Generation Benchmark

no code implementations CVPR 2025 Hui Han, Siyuan Li, Jiaqi Chen, Yiwen Yuan, Yuling Wu, Yufan Deng, Chak Tou Leong, Hanwen Du, Junchen Fu, Youhua Li, Jie Zhang, Chi Zhang, Li-Jia Li, Yongxin Ni

This benchmark represents the first attempt to systematically leverage MLLMs across all dimensions relevant to video generation assessment in generative models.

Large Language Model Video Generation

AVF-MAE++: Scaling Affective Video Facial Masked Autoencoders via Efficient Audio-Visual Self-Supervised Learning

1 code implementation CVPR 2025 Xuecheng Wu, Heli Sun, Yifan Wang, Jiayu Nie, Jie Zhang, Yabing Wang, Junxiao Xue, Liang He

To tackle these gaps, we introduce AVF-MAE++, a series audio-visual MAE designed to explore the impact of scaling on AVFA with a focus on advanced correlation modeling.

Self-Supervised Learning

M$^3$oralBench: A MultiModal Moral Benchmark for LVLMs

1 code implementation30 Dec 2024 Bei Yan, Jie Zhang, ZhiYuan Chen, Shiguang Shan, Xilin Chen

To bridge this gap, we introduce M$^3$oralBench, the first MultiModal Moral Benchmark for LVLMs.

Moral Scenarios

EraseAnything: Enabling Concept Erasure in Rectified Flow Transformers

1 code implementation29 Dec 2024 Daiheng Gao, Shilin Lu, Shaw Walters, Wenbo Zhou, Jiaming Chu, Jie Zhang, Bang Zhang, Mengxi Jia, Jian Zhao, Zhaoxin Fan, Weiming Zhang

Removing unwanted concepts from large-scale text-to-image (T2I) diffusion models while maintaining their overall generative quality remains an open challenge.

Contrastive Learning

Multi-P$^2$A: A Multi-perspective Benchmark on Privacy Assessment for Large Vision-Language Models

1 code implementation27 Dec 2024 Jie Zhang, Xiangkui Cao, Zhouyu Han, Shiguang Shan, Xilin Chen

Multi-P$^2$A covers 26 categories of personal privacy, 15 categories of trade secrets, and 18 categories of state secrets, totaling 31, 962 samples.

Multi-Granularity Open Intent Classification via Adaptive Granular-Ball Decision Boundary

1 code implementation18 Dec 2024 Yanhua Li, Xiaocao Ouyang, Chaofan Pan, Jie Zhang, Sen Zhao, Shuyin Xia, Xin Yang, Guoyin Wang, Tianrui Li

To tackle these issues, we propose a Multi-granularity Open intent classification method via adaptive Granular-Ball decision boundary (MOGB).

Classification intent-classification +2

RepFace: Refining Closed-Set Noise with Progressive Label Correction for Face Recognition

no code implementations16 Dec 2024 Jie Zhang, Xun Gong, Zhonglin Sun

However, face recognition performance is heavily affected by the label noise, especially closed-set noise.

Face Recognition

Active Large Language Model-based Knowledge Distillation for Session-based Recommendation

no code implementations15 Dec 2024 Yingpeng Du, Zhu Sun, Ziyan Wang, Haoyan Chua, Jie Zhang, Yew-Soon Ong

Knowledge distillation (KD)-based methods can alleviate these issues by transferring the knowledge to a small student, which trains a student based on the predictions of a cumbersome teacher.

Active Learning Knowledge Distillation +4

SuperMark: Robust and Training-free Image Watermarking via Diffusion-based Super-Resolution

no code implementations13 Dec 2024 Runyi Hu, Jie Zhang, Yiming Li, Jiwei Li, Qing Guo, Han Qiu, Tianwei Zhang

For extraction, the process is reversed: the watermarked image is inverted back to the initial watermarked noise via DDIM Inversion, from which the embedded watermark is extracted.

Denoising Super-Resolution

FaceTracer: Unveiling Source Identities from Swapped Face Images and Videos for Fraud Prevention

no code implementations11 Dec 2024 Zhongyi Zhang, Jie Zhang, Wenbo Zhou, Xinghui Zhou, Qing Guo, Weiming Zhang, Tianwei Zhang, Nenghai Yu

Face-swapping techniques have advanced rapidly with the evolution of deep learning, leading to widespread use and growing concerns about potential misuse, especially in cases of fraud.

Disentanglement Face Swapping

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents

no code implementations11 Dec 2024 Yun Xing, Nhat Chung, Jie Zhang, Yue Cao, Ivor Tsang, Yang Liu, Lei Ma, Qing Guo

We validate our method on both digital and physical level, \ie, nuImage and manually captured real scenes, where both statistical and visual results prove that our MAGIC is powerful and effectively for attacking wide-used object detection systems.

object-detection Object Detection +2

Reinforcement Learning Enhanced LLMs: A Survey

1 code implementation5 Dec 2024 Shuhe Wang, Shengyu Zhang, Jie Zhang, Runyi Hu, Xiaoya Li, Tianwei Zhang, Jiwei Li, Fei Wu, Guoyin Wang, Eduard Hovy

This paper surveys research in the rapidly growing field of enhancing large language models (LLMs) with reinforcement learning (RL), a technique that enables LLMs to improve their performance by receiving feedback in the form of rewards based on the quality of their outputs, allowing them to generate more accurate, coherent, and contextually appropriate responses.

reinforcement-learning Reinforcement Learning +2

Physics-informed Deep Learning for Muscle Force Prediction with Unlabeled sEMG Signals

no code implementations5 Dec 2024 Shuhao Ma, Jie Zhang, Chaoyang Shi, Pei Di, Ian D. Robertson, Zhi-Qiang Zhang

To achieve this, the Hill muscle model-based forward dynamics is embedded into the deep neural network as the additional loss to further regulate the behavior of the deep neural network.

Muscle Force Prediction

MRP-LLM: Multitask Reflective Large Language Models for Privacy-Preserving Next POI Recommendation

no code implementations3 Dec 2024 Ziqing Wu, Zhu Sun, Dongxia Wang, Lu Zhang, Jie Zhang, Yew Soon Ong

The Neighbor Preference Retrieval Module retrieves and summarizes the preferences of similar users from the KB to obtain collaborative signals.

Language Modeling Language Modelling +2

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images

1 code implementation CVPR 2025 Aniruddha Ganguly, Debolina Chatterjee, Wentao Huang, Jie Zhang, Alisa Yurovsky, Travis Steele Johnson, Chao Chen

Recent advances in Spatial Transcriptomics (ST) pair histology images with spatially resolved gene expression profiles, enabling predictions of gene expression across different tissue locations based on image patches.

graph construction Prediction

Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey

no code implementations3 Dec 2024 Yunkai Dang, Kaichen Huang, Jiahao Huo, Yibo Yan, Sirui Huang, Dongrui Liu, Mengxi Gao, Jie Zhang, Chen Qian, Kun Wang, Yong liu, Jing Shao, Hui Xiong, Xuming Hu

The rapid development of Artificial Intelligence (AI) has revolutionized numerous fields, with large language models (LLMs) and computer vision (CV) systems driving advancements in natural language understanding and visual processing, respectively.

Cross-Modal Retrieval Natural Language Understanding +4

From ChebNet to ChebGibbsNet

1 code implementation2 Dec 2024 Jie Zhang, Min-Te Sun

Different polynomial bases, such as Bernstein, Chebyshev, and monomial basis, have various convergence rates that will affect the error in polynomial interpolation.

Graph Representation Learning Node Classification

SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments

no code implementations CVPR 2025 Yue Cao, Yun Xing, Jie Zhang, Di Lin, Tianwei Zhang, Ivor Tsang, Yang Liu, Qing Guo

In this paper, we present the first approach to generate scene-coherent typographic adversarial attacks that mislead advanced LVLMs while maintaining visual naturalness through the capability of the LLM-based agent.

Adversarial Text Scene Understanding

Enhancing Low Dose Computed Tomography Images Using Consistency Training Techniques

no code implementations19 Nov 2024 Mahmut S. Gokmen, Jie Zhang, Ge Wang, Jin Chen, Cody Bumgardner

This is combined with a sinusoidal curriculum that enhances the learning of the trajectory between the noise distribution and the posterior distribution of interest, allowing High Noise Improved Consistency Training (HN-iCT) to be trained in a supervised fashion.

Image Inpainting Unconditional Image Generation

Semantic or Covariate? A Study on the Intractable Case of Out-of-Distribution Detection

no code implementations18 Nov 2024 Xingming Long, Jie Zhang, Shiguang Shan, Xilin Chen

The primary goal of out-of-distribution (OOD) detection tasks is to identify inputs with semantic shifts, i. e., if samples from novel classes are absent in the in-distribution (ID) dataset used for training, we should reject these OOD samples rather than misclassifying them into existing ID classes.

Out-of-Distribution Detection Out of Distribution (OOD) Detection

Spider: Any-to-Many Multimodal LLM

1 code implementation14 Nov 2024 Jinxiang Lai, Jie Zhang, Jun Liu, Jian Li, Xiaocheng Lu, Song Guo

To address this limitation, we introduce Spider, a novel efficient Any-to-Many Modalities Generation (AMMG) framework, which can generate an arbitrary combination of modalities 'Text + Xs', such as Text + {Image and Audio and Video}.

multimodal interaction

Advancing Sustainability via Recommender Systems: A Survey

1 code implementation12 Nov 2024 Xin Zhou, Lei Zhang, Honglei Zhang, Yixin Zhang, Xiaoxiong Zhang, Jie Zhang, Zhiqi Shen

Human behavioral patterns and consumption paradigms have emerged as pivotal determinants in environmental degradation and climate change, with quotidian decisions pertaining to transportation, energy utilization, and resource consumption collectively precipitating substantial ecological impacts.

Recommendation Systems Survey

Confidence Aware Learning for Reliable Face Anti-spoofing

no code implementations2 Nov 2024 Xingming Long, Jie Zhang, Shiguang Shan

The prediction confidence for each sample is subsequently assessed using the Mahalanobis distance between the sample and the Gaussians for the "known data".

Face Anti-Spoofing Prediction +1

Learning to Handle Complex Constraints for Vehicle Routing Problems

1 code implementation28 Oct 2024 Jieyi Bi, Yining Ma, Jianan Zhou, Wen Song, Zhiguang Cao, Yaoxin Wu, Jie Zhang

Vehicle Routing Problems (VRPs) can model many real-world scenarios and often involve complex constraints.

Decoder Traveling Salesman Problem

DEAN: Deactivating the Coupled Neurons to Mitigate Fairness-Privacy Conflicts in Large Language Models

1 code implementation22 Oct 2024 Chen Qian, Dongrui Liu, Jie Zhang, Yong liu, Jing Shao

Extensive experimental results demonstrate that DEAN eliminates the trade-off phenomenon and significantly improves LLMs' fairness and privacy awareness simultaneously, \eg improving Qwen-2-7B-Instruct's fairness awareness by 12. 2\% and privacy awareness by 14. 0\%.

Fairness

SurgeryV2: Bridging the Gap Between Model Merging and Multi-Task Learning with Deep Representation Surgery

1 code implementation18 Oct 2024 Enneng Yang, Li Shen, Zhenyi Wang, Guibing Guo, Xingwei Wang, Xiaocun Cao, Jie Zhang, DaCheng Tao

However, in this paper, we examine the merged model's representation distribution and uncover a critical issue of "representation bias".

Multi-Task Learning

REEF: Representation Encoding Fingerprints for Large Language Models

1 code implementation18 Oct 2024 Jie Zhang, Dongrui Liu, Chen Qian, Linfeng Zhang, Yong liu, Yu Qiao, Jing Shao

Therefore, model owners and third parties need to identify whether a suspect model is a subsequent development of the victim model.

SiFiSinger: A High-Fidelity End-to-End Singing Voice Synthesizer based on Source-filter Model

no code implementations16 Oct 2024 Jianwei Cui, Yu Gu, Chao Weng, Jie Zhang, Liping Chen, LiRong Dai

This paper presents an advanced end-to-end singing voice synthesis (SVS) system based on the source-filter mechanism that directly translates lyrical and melodic cues into expressive and high-fidelity human-like singing.

Decoder Singing Voice Synthesis

Towards Reliable Verification of Unauthorized Data Usage in Personalized Text-to-Image Diffusion Models

1 code implementation14 Oct 2024 Boheng Li, Yanhao Wei, Yankai Fu, Zhenting Wang, Yiming Li, Jie Zhang, Run Wang, Tianwei Zhang

In this paper, we introduce SIREN, a novel methodology to proactively trace unauthorized data usage in black-box personalized text-to-image diffusion models.

Wireless-Friendly Window Position Optimization for RIS-Aided Outdoor-to-Indoor Networks based on Multi-Modal Large Language Model

no code implementations7 Oct 2024 Jinbo Hou, Kehai Qiu, Zitian Zhang, Yong Yu, Kezhi Wang, Stefano Capolongo, Jiliang Zhang, Zeyang Li, Jie Zhang

This paper aims to simultaneously optimize indoor wireless and daylight performance by adjusting the positions of windows and the beam directions of window-deployed reconfigurable intelligent surfaces (RISs) for RIS-aided outdoor-to-indoor (O2I) networks utilizing large language models (LLM) as optimizers.

Language Modeling Language Modelling +2

Collaboration! Towards Robust Neural Methods for Routing Problems

1 code implementation7 Oct 2024 Jianan Zhou, Yaoxin Wu, Zhiguang Cao, Wen Song, Jie Zhang, Zhiqi Shen

Given a neural VRP method, we adversarially train multiple models in a collaborative manner to synergistically promote robustness against attacks, while boosting standard generalization on clean instances.

Out-of-Distribution Generalization

Multiscale Latent Diffusion Model for Enhanced Feature Extraction from Medical Images

no code implementations5 Oct 2024 Rabeya Tus Sadia, Jie Zhang, Jin Chen

In response to these challenges, we propose LTDiff++, a multiscale latent diffusion model designed to enhance feature extraction in medical imaging.

Anatomy Computed Tomography (CT) +1

Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data

no code implementations29 Sep 2024 Jie Zhang, Debeshee Das, Gautam Kamath, Florian Tramèr

We argue that this approach is fundamentally unsound: to provide convincing evidence, the data creator needs to demonstrate that their attack has a low false positive rate, i. e., that the attack's output is unlikely under the null hypothesis that the model was not trained on the target data.

Face Forgery Detection with Elaborate Backbone

1 code implementation25 Sep 2024 Zonghui Guo, Yingjie Liu, Jie Zhang, Haiyong Zheng, Shiguang Shan

Specifically, we analyze the crucial contributions of backbones with different configurations in FFD task and propose leveraging the ViT network with self-supervised learning on real-face datasets to pre-train a backbone, equipping it with superior facial representation capabilities.

DeepFake Detection Face Generation +2

Mean Age of Information in Partial Offloading Mobile Edge Computing Networks

no code implementations24 Sep 2024 Ying Dong, Hang Xiao, Haonan Hu, Jiliang Zhang, Qianbin Chen, Jie Zhang

The results show that by jointly optimising the COR and TGR, the partial offloading scheme outperforms the local and remote computing schemes in terms of the MAoI, which can be improved by up to 51% and 61%, respectively.

Edge-computing

LiSenNet: Lightweight Sub-band and Dual-Path Modeling for Real-Time Speech Enhancement

1 code implementation20 Sep 2024 Haoyin Yan, Jie Zhang, Cunhang Fan, Yeping Zhou, Peiqi Liu

Speech enhancement (SE) aims to extract the clean waveform from noise-contaminated measurements to improve the speech quality and intelligibility.

Speech Enhancement

Geometry-Constrained EEG Channel Selection for Brain-Assisted Speech Enhancement

no code implementations19 Sep 2024 Keying Zuo, Qingtian Xu, Jie Zhang, ZhenHua Ling

Brain-assisted speech enhancement (BASE) aims to extract the target speaker in complex multi-talker scenarios using electroencephalogram (EEG) signals as an assistive modality, as the auditory attention of the listener can be decoded from electroneurographic signals of the brain.

channel selection EEG +1

A Lightweight and Real-Time Binaural Speech Enhancement Model with Spatial Cues Preservation

1 code implementation19 Sep 2024 Jingyuan Wang, Jie Zhang, Shihao Chen, Miao Sun

Binaural speech enhancement (BSE) aims to jointly improve the speech quality and intelligibility of noisy signals received by hearing devices and preserve the spatial cues of the target for natural listening.

Speech Enhancement

InstInfer: In-Storage Attention Offloading for Cost-Effective Long-Context LLM Inference

no code implementations8 Sep 2024 Xiurui Pan, Endian Li, Qiao Li, Shengwen Liang, Yizhou Shan, Ke Zhou, Yingwei Luo, Xiaolin Wang, Jie Zhang

Several cost-effective solutions leverage host memory or SSDs to reduce storage costs for offline inference scenarios and improve the throughput.

Edge-computing

Spindle: Efficient Distributed Training of Multi-Task Large Models via Wavefront Scheduling

no code implementations5 Sep 2024 Yujie Wang, Shenhan Zhu, Fangcheng Fu, Xupeng Miao, Jie Zhang, Juan Zhu, Fan Hong, Yong Li, Bin Cui

Recent foundation models are capable of handling multiple tasks and multiple data modalities with the unified base model structure and several specialized model components.

Management model +1

Shuffle Mamba: State Space Models with Random Shuffle for Multi-Modal Image Fusion

no code implementations3 Sep 2024 Ke Cao, Xuanhua He, Tao Hu, Chengjun Xie, Jie Zhang, Man Zhou, Danfeng Hong

Multi-modal image fusion integrates complementary information from different modalities to produce enhanced and informative images.

Long-range modeling Mamba +1

Optimal Dispatch Strategy for a Multi-microgrid Cooperative Alliance Using a Two-Stage Pricing Mechanism

no code implementations23 Aug 2024 Yonghui Nie, Zhi Li, Jie Zhang, Lei Gao, Yang Li, Hengyu Zhou

To coordinate resources among multi-level stakeholders and enhance the integration of electric vehicles (EVs) into multi-microgrids, this study proposes an optimal dispatch strategy within a multi-microgrid cooperative alliance using a nuanced two-stage pricing mechanism.

Scheduling

LCM-SVC: Latent Diffusion Model Based Singing Voice Conversion with Inference Acceleration via Latent Consistency Distillation

no code implementations22 Aug 2024 Shihao Chen, Yu Gu, Jianwei Cui, Jie Zhang, Rilin Chen, LiRong Dai

We achieved one-step or few-step inference while maintaining the high performance by distilling a pre-trained LDM based SVC model, which had the advantages of timbre decoupling and sound quality.

Voice Conversion

Empowering Wireless Network Applications with Deep Learning-based Radio Propagation Models

no code implementations22 Aug 2024 Stefanos Bakirtzis, Cagkan Yapar, Marco Fiore, Jie Zhang, Ian Wassell

The efficient deployment and operation of any wireless communication ecosystem rely on knowledge of the received signal quality over the target coverage area.

Deep Learning

Non-Homophilic Graph Pre-Training and Prompt Learning

1 code implementation22 Aug 2024 Xingtong Yu, Jie Zhang, Yuan Fang, Renhe Jiang

In particular, many real-world graphs are non-homophilic, not strictly or uniformly homophilic with mixing homophilic and heterophilic patterns, exhibiting varying non-homophilic characteristics across graphs and nodes.

Prompt Learning

GenderCARE: A Comprehensive Framework for Assessing and Reducing Gender Bias in Large Language Models

1 code implementation22 Aug 2024 Kunsheng Tang, Wenbo Zhou, Jie Zhang, Aishan Liu, Gelei Deng, Shuai Li, Peigui Qi, Weiming Zhang, Tianwei Zhang, Nenghai Yu

By offering a realistic assessment and tailored reduction of gender biases, we hope that our GenderCARE can represent a significant step towards achieving fairness and equity in LLMs.

counterfactual Data Augmentation +2

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities

1 code implementation14 Aug 2024 Enneng Yang, Li Shen, Guibing Guo, Xingwei Wang, Xiaochun Cao, Jie Zhang, DaCheng Tao

Model merging is an efficient empowerment technique in the machine learning community that does not require the collection of raw training data and does not require expensive computation.

Continual Learning Few-Shot Learning +1

The Crowd in MOOCs: A Study of Learning Patterns at Scale

no code implementations6 Aug 2024 Xin Zhou, Aixin Sun, Jie Zhang, Donghui Lin

The increasing availability of learning activity data in Massive Open Online Courses (MOOCs) enables us to conduct a large-scale analysis of learners' learning behavior.

Sequential Pattern Mining

Training-Free Large Model Priors for Multiple-in-One Image Restoration

no code implementations18 Jul 2024 Xuanhua He, Lang Li, Yingying Wang, Hui Zheng, Ke Cao, Keyu Yan, Rui Li, Chengjun Xie, Jie Zhang, Man Zhou

To address this issue, we propose Large Model Driven Image Restoration framework (LMDIR), a novel multiple-in-one image restoration paradigm that leverages the generic priors from large multi-modal language models (MMLMs) and the pretrained diffusion models.

Image Restoration

The Better Angels of Machine Personality: How Personality Relates to LLM Safety

1 code implementation17 Jul 2024 Jie Zhang, Dongrui Liu, Chen Qian, Ziyue Gan, Yong liu, Yu Qiao, Jing Shao

In this paper, we discover that LLMs' personality traits are closely related to their safety abilities, i. e., toxicity, privacy, and fairness, based on the reliable MBTI-M scale.

Fairness Safety Alignment

T2IShield: Defending Against Backdoors on Text-to-Image Diffusion Models

1 code implementation5 Jul 2024 Zhongqi Wang, Jie Zhang, Shiguang Shan, Xilin Chen

In this paper, for the first time, we propose a comprehensive defense method named T2IShield to detect, localize, and mitigate such attacks.

Backdoor Attack

The USTC-NERCSLIP Systems for The ICMC-ASR Challenge

no code implementations2 Jul 2024 Minghui Wu, Luzhen Xu, Jie Zhang, Haitao Tang, Yanyan Yue, Ruizhi Liao, Jintao Zhao, Zhengzhe Zhang, Yichi Wang, Haoyin Yan, Hongliang Yu, Tongle Ma, Jiachen Liu, Chongliang Wu, Yongchao Li, Yanyong Zhang, Xin Fang, Yue Zhang

This report describes the submitted system to the In-Car Multi-Channel Automatic Speech Recognition (ICMC-ASR) challenge, which considers the ASR task with multi-speaker overlapping and Mandarin accent dynamics in the ICMC case.

Automatic Speech Recognition Pseudo Label +5

Complementary Fusion of Deep Network and Tree Model for ETA Prediction

no code implementations1 Jul 2024 Yurui Huang, Jie Zhang, HengDa Bao, Yang Yang, Jian Yang

Estimated time of arrival (ETA) is a very important factor in the transportation system.

Decision Transformer for IRS-Assisted Systems with Diffusion-Driven Generative Channels

no code implementations28 Jun 2024 Jie Zhang, Jun Li, Zhe Wang, Yu Han, Long Shi, Bin Cao

In this paper, we propose a novel diffusion-decision transformer (D2T) architecture to optimize the beamforming strategies for intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) communication systems.

Reinforcement Learning (RL)

Dysca: A Dynamic and Scalable Benchmark for Evaluating Perception Ability of LVLMs

2 code implementations27 Jun 2024 Jie Zhang, Zhongqi Wang, Mengqi Lei, Zheng Yuan, Bei Yan, Shiguang Shan, Xilin Chen

Currently many benchmarks have been proposed to evaluate the perception ability of the Large Vision-Language Models (LVLMs).

Evaluating the Quality of Hallucination Benchmarks for Large Vision-Language Models

1 code implementation24 Jun 2024 Bei Yan, Jie Zhang, Zheng Yuan, Shiguang Shan, Xilin Chen

Furthermore, based on the results of our quality measurement, we construct a High-Quality Hallucination Benchmark (HQH) for LVLMs, which demonstrates superior reliability and validity under our HQM framework.

Hallucination

Blind Baselines Beat Membership Inference Attacks for Foundation Models

1 code implementation23 Jun 2024 Debeshee Das, Jie Zhang, Florian Tramèr

Membership inference (MI) attacks try to determine if a data sample was used to train a machine learning model.

Machine Unlearning

VLBiasBench: A Comprehensive Benchmark for Evaluating Bias in Large Vision-Language Model

1 code implementation20 Jun 2024 Sibo Wang, Xiangkui Cao, Jie Zhang, Zheng Yuan, Shiguang Shan, Xilin Chen, Wen Gao

The emergence of Large Vision-Language Models (LVLMs) marks significant strides towards achieving general artificial intelligence.

Language Modeling Language Modelling

AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents

1 code implementation19 Jun 2024 Edoardo Debenedetti, Jie Zhang, Mislav Balunović, Luca Beurer-Kellner, Marc Fischer, Florian Tramèr

Unfortunately, AI agents are vulnerable to prompt injection attacks where data returned by external tools hijacks the agent to execute malicious tasks.

Textual Unlearning Gives a False Sense of Unlearning

no code implementations19 Jun 2024 Jiacheng Du, Zhibo Wang, Jie Zhang, Xiaoyi Pang, Jiahui Hu, Kui Ren

Language Models (LMs) are prone to ''memorizing'' training data, including substantial sensitive user information.

Machine Unlearning

Rethinking the Evaluation of Out-of-Distribution Detection: A Sorites Paradox

1 code implementation14 Jun 2024 Xingming Long, Jie Zhang, Shiguang Shan, Xilin Chen

In this paper, we construct a benchmark named Incremental Shift OOD (IS-OOD) to address the issue, in which we divide the test samples into subsets with different semantic and covariate shift degrees relative to the ID dataset.

Out-of-Distribution Detection Out of Distribution (OOD) Detection

Refining Self-Supervised Learnt Speech Representation using Brain Activations

no code implementations12 Jun 2024 Hengyu Li, Kangdi Mei, Zhaoci Liu, Yang Ai, Liping Chen, Jie Zhang, ZhenHua Ling

It was shown in literature that speech representations extracted by self-supervised pre-trained models exhibit similarities with brain activations of human for speech perception and fine-tuning speech representation models on downstream tasks can further improve the similarity.

Automatic Speech Recognition Speaker Verification +2

LDM-SVC: Latent Diffusion Model Based Zero-Shot Any-to-Any Singing Voice Conversion with Singer Guidance

no code implementations8 Jun 2024 Shihao Chen, Yu Gu, Jie Zhang, Na Li, Rilin Chen, Liping Chen, LiRong Dai

We pretrain a variational autoencoder structure using the noted open-source So-VITS-SVC project based on the VITS framework, which is then used for the LDM training.

Voice Conversion

Anonymization Prompt Learning for Facial Privacy-Preserving Text-to-Image Generation

no code implementations27 May 2024 Liang Shi, Jie Zhang, Shiguang Shan

Specifically, we train a learnable prompt prefix for text-to-image diffusion models, which forces the model to generate anonymized facial identities, even when prompted to produce images of specific individuals.

Face Swapping Privacy Preserving +3

ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign Users

1 code implementation24 May 2024 Guanlin Li, Kangjie Chen, Shudong Zhang, Jie Zhang, Tianwei Zhang

Additionally, we introduce three large-scale red-teaming datasets for studying the safety risks associated with text-to-image models.

Diversity Language Modeling +3

Unlearning during Learning: An Efficient Federated Machine Unlearning Method

1 code implementation24 May 2024 Hanlin Gu, Gongxi Zhu, Jie Zhang, Xinyuan Zhao, Yuxing Han, Lixin Fan, Qiang Yang

To facilitate the implementation of the right to be forgotten, the concept of federated machine unlearning (FMU) has also emerged.

Federated Learning Machine Unlearning

Towards Transferable Attacks Against Vision-LLMs in Autonomous Driving with Typography

no code implementations23 May 2024 Nhat Chung, Sensen Gao, Tuan-Anh Vu, Jie Zhang, Aishan Liu, Yun Lin, Jin Song Dong, Qing Guo

To further explore the risk in AD systems and the transferability of practical threats, we propose to leverage typographic attacks against AD systems relying on the decision-making capabilities of Vision-LLMs.

Autonomous Driving Decision Making

BIMM: Brain Inspired Masked Modeling for Video Representation Learning

1 code implementation21 May 2024 Zhifan Wan, Jie Zhang, Changzhen Li, Shiguang Shan

The visual pathway of human brain includes two sub-pathways, ie, the ventral pathway and the dorsal pathway, which focus on object identification and dynamic information modeling, respectively.

Representation Learning

Image to Pseudo-Episode: Boosting Few-Shot Segmentation by Unlabeled Data

no code implementations14 May 2024 Jie Zhang, Yuhan Li, Yude Wang, Stephen Lin, Shiguang Shan

Few-shot segmentation (FSS) aims to train a model which can segment the object from novel classes with a few labeled samples.

Data Augmentation Pseudo Label

Cross-Domain Continual Learning via CLAMP

1 code implementation12 May 2024 Weiwei Weng, Mahardhika Pratama, Jie Zhang, Chen Chen, Edward Yapp Kien Yee, Ramasamy Savitha

To this end, this article proposes a cross-domain CL approach making possible to deploy a single model in such environments without additional labelling costs.

Continual Learning Domain Adaptation +2

LMVD: A Large-Scale Multimodal Vlog Dataset for Depression Detection in the Wild

2 code implementations9 May 2024 Lang He, Kai Chen, Junnan Zhao, Yimeng Wang, Ercheng Pei, Haifeng Chen, Jiewei Jiang, Shiqing Zhang, Jie Zhang, Zhongmin Wang, Tao He, Prayag Tiwari

Depression can significantly impact many aspects of an individual's life, including their personal and social functioning, academic and work performance, and overall quality of life.

Depression Detection Navigate

When LLMs Meet Cybersecurity: A Systematic Literature Review

1 code implementation6 May 2024 Jie Zhang, Haoyu Bu, Hui Wen, Yongji Liu, Haiqiang Fei, Rongrong Xi, Lun Li, Yun Yang, Hongsong Zhu, Dan Meng

The rapid development of large language models (LLMs) has opened new avenues across various fields, including cybersecurity, which faces an evolving threat landscape and demand for innovative technologies.

Systematic Literature Review

Evaluations of Machine Learning Privacy Defenses are Misleading

2 code implementations26 Apr 2024 Michael Aerni, Jie Zhang, Florian Tramèr

Empirical defenses for machine learning privacy forgo the provable guarantees of differential privacy in the hope of achieving higher utility while resisting realistic adversaries.

Dual Expert Distillation Network for Generalized Zero-Shot Learning

1 code implementation25 Apr 2024 Zhijie Rao, Jingcai Guo, Xiaocheng Lu, Jingming Liang, Jie Zhang, Haozhao Wang, Kang Wei, Xiaofeng Cao

Zero-shot learning has consistently yielded remarkable progress via modeling nuanced one-to-one visual-attribute correlation.

Attribute Generalized Zero-Shot Learning

ID-Animator: Zero-Shot Identity-Preserving Human Video Generation

1 code implementation23 Apr 2024 Xuanhua He, Quande Liu, Shengju Qian, Xin Wang, Tao Hu, Ke Cao, Keyu Yan, Jie Zhang

In this study, we present \textbf{ID-Animator}, a zero-shot human-video generation approach that can perform personalized video generation given a single reference facial image without further training.

Attribute Video Generation

High Noise Scheduling is a Must

no code implementations9 Apr 2024 Mahmut S. Gokmen, Cody Bumgardner, Jie Zhang, Ge Wang, Jin Chen

The results show that the polynomial noise distribution outperforms the model trained with log-normal noise distribution, yielding a 33. 54 FID score after 100, 000 training steps with constant discretization steps.

Denoising Image Generation +1

Decision Transformers for Wireless Communications: A New Paradigm of Resource Management

no code implementations8 Apr 2024 Jie Zhang, Jun Li, Long Shi, Zhe Wang, Shi Jin, Wen Chen, H. Vincent Poor

By leveraging the power of DT models learned over offline datasets, the proposed architecture is expected to achieve rapid convergence with many fewer training epochs and higher performance in new scenarios with different state and action spaces, compared with DRL.

Deep Reinforcement Learning Edge-computing +2

Jailbreaking Prompt Attack: A Controllable Adversarial Attack against Diffusion Models

no code implementations2 Apr 2024 Jiachen Ma, Yijiang Li, Zhiqing Xiao, Anda Cao, Jie Zhang, Chao Ye, Junbo Zhao

In this work, we investigate a more practical and universal attack that does not require the presence of a target model and demonstrate that the high-dimensional text embedding space inherently contains NSFW concepts that can be exploited to generate harmful images.

Adversarial Attack Text to Image Generation +1

How memories are stored in the brain: the declarative memory model

no code implementations25 Mar 2024 Jie Zhang

The ability to form memories is a basic feature of learning and accumulating knowledge.

RU22Fact: Optimizing Evidence for Multilingual Explainable Fact-Checking on Russia-Ukraine Conflict

1 code implementation25 Mar 2024 Yirong Zeng, Xiao Ding, Yi Zhao, Xiangyu Li, Jie Zhang, Chao Yao, Ting Liu, Bing Qin

Furthermore, we construct RU22Fact, a novel multilingual explainable fact-checking dataset on the Russia-Ukraine conflict in 2022 of 16K samples, each containing real-world claims, optimized evidence, and referenced explanation.

16k Claim Verification +5

Re2LLM: Reflective Reinforcement Large Language Model for Session-based Recommendation

no code implementations25 Mar 2024 Ziyan Wang, Yingpeng Du, Zhu Sun, Haoyan Chua, Kaidong Feng, Wenya Wang, Jie Zhang

However, the former methods struggle with optimal prompts to elicit the correct reasoning of LLMs due to the lack of task-specific feedback, leading to unsatisfactory recommendations.

Language Modeling Language Modelling +2

DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning

no code implementations CVPR 2024 Sikai Bai, Jie Zhang, Shuaicheng Li, Song Guo, Jingcai Guo, Jun Hou, Tao Han, Xiaocheng Lu

Federated learning (FL) has emerged as a powerful paradigm for learning from decentralized data, and federated domain generalization further considers the test dataset (target domain) is absent from the decentralized training data (source domains).

Domain Generalization Federated Learning +1

DiffClass: Diffusion-Based Class Incremental Learning

no code implementations8 Mar 2024 Zichong Meng, Jie Zhang, Changdi Yang, Zheng Zhan, Pu Zhao, Yanzhi Wang

On top of that, Exemplar-free Class Incremental Learning is even more challenging due to forbidden access to previous task data.

class-incremental learning Class Incremental Learning +4

RSAM-Seg: A SAM-based Approach with Prior Knowledge Integration for Remote Sensing Image Semantic Segmentation

no code implementations29 Feb 2024 Jie Zhang, Xubing Yang, Rui Jiang, Wei Shao, Li Zhang

While the direct application of SAM to remote sensing image segmentation tasks does not yield satisfactory results, we propose RSAM-Seg, which stands for Remote Sensing SAM with Semantic Segmentation, as a tailored modification of SAM for the remote sensing field and eliminates the need for manual intervention to provide prompts.

Cloud Detection Image Segmentation +2

Towards Tracing Trustworthiness Dynamics: Revisiting Pre-training Period of Large Language Models

1 code implementation29 Feb 2024 Chen Qian, Jie Zhang, Wei Yao, Dongrui Liu, Zhenfei Yin, Yu Qiao, Yong liu, Jing Shao

This research provides an initial exploration of trustworthiness modeling during LLM pre-training, seeking to unveil new insights and spur further developments in the field.

Fairness Mutual Information Estimation

Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Merging

2 code implementations28 Feb 2024 Wei zhang, Xiangyuan Guan, Lu Yunhong, Jie Zhang, Shuangyong Song, Xianfu Cheng, Zhenhe Wu, Zhoujun Li

Log parsing, which entails transforming raw log messages into structured templates, constitutes a critical phase in the automation of log analytics.

Log Parsing

Model X-ray:Detecting Backdoored Models via Decision Boundary

1 code implementation27 Feb 2024 Yanghao Su, Jie Zhang, Ting Xu, Tianwei Zhang, Weiming Zhang, Nenghai Yu

By accessing the model to obtain hard labels, we construct decision boundaries within the convex combination of three samples.

Diagnostic

Pan-Mamba: Effective pan-sharpening with State Space Model

1 code implementation19 Feb 2024 Xuanhua He, Ke Cao, Keyu Yan, Rui Li, Chengjun Xie, Jie Zhang, Man Zhou

To the best of our knowledge, this work is the first attempt in exploring the potential of the Mamba model and establishes a new frontier in the pan-sharpening techniques.

Mamba Pansharpening

Towards Cross-Domain Continual Learning

1 code implementation19 Feb 2024 Marcus de Carvalho, Mahardhika Pratama, Jie Zhang, Chua Haoyan, Edward Yapp

In this work, we introduce a novel approach called Cross-Domain Continual Learning (CDCL) that addresses the limitations of being limited to single supervised domains.

Continual Learning

SIBO: A Simple Booster for Parameter-Efficient Fine-Tuning

no code implementations19 Feb 2024 Zhihao Wen, Jie Zhang, Yuan Fang

Fine-tuning all parameters of large language models (LLMs) necessitates substantial computational power and extended time.

parameter-efficient fine-tuning

Large Language Model with Graph Convolution for Recommendation

no code implementations14 Feb 2024 Yingpeng Du, Ziyan Wang, Zhu Sun, Haoyan Chua, Hongzhi Liu, Zhonghai Wu, Yining Ma, Jie Zhang, Youchen Sun

To adapt text-based LLMs with structured graphs, We use the LLM as an aggregator in graph processing, allowing it to understand graph-based information step by step.

Hallucination Language Modeling +2

Symbol: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning

1 code implementation4 Feb 2024 Jiacheng Chen, Zeyuan Ma, Hongshu Guo, Yining Ma, Jie Zhang, Yue-Jiao Gong

Recent Meta-learning for Black-Box Optimization (MetaBBO) methods harness neural networks to meta-learn configurations of traditional black-box optimizers.

Meta-Learning Zero-shot Generalization

PRIME: Protect Your Videos From Malicious Editing

1 code implementation2 Feb 2024 Guanlin Li, Shuai Yang, Jie Zhang, Tianwei Zhang

With the development of generative models, the quality of generated content keeps increasing.

Multi-granularity Correspondence Learning from Long-term Noisy Videos

1 code implementation30 Jan 2024 Yijie Lin, Jie Zhang, Zhenyu Huang, Jia Liu, Zujie Wen, Xi Peng

Existing video-language studies mainly focus on learning short video clips, leaving long-term temporal dependencies rarely explored due to over-high computational cost of modeling long videos.

Action Segmentation Long Video Retrieval (Background Removed) +2

Adversarial speech for voice privacy protection from Personalized Speech generation

no code implementations22 Jan 2024 Shihao Chen, Liping Chen, Jie Zhang, KongAik Lee, ZhenHua Ling, LiRong Dai

For validation, we employ the open-source pre-trained YourTTS model for speech generation and protect the target speaker's speech in the white-box scenario.

Speaker Verification text-to-speech +2

CBVS: A Large-Scale Chinese Image-Text Benchmark for Real-World Short Video Search Scenarios

1 code implementation19 Jan 2024 Xiangshuo Qiao, Xianxin Li, Xiaozhe Qu, Jie Zhang, Yang Liu, Yu Luo, Cihang Jin, Jin Ma

Differently, video covers in short video search scenarios are presented as user-originated contents that provide important visual summaries of videos.

Common Sense Reasoning Image Retrieval

Generalized Face Liveness Detection via De-fake Face Generator

1 code implementation17 Jan 2024 Xingming Long, Jie Zhang, Shiguang Shan

Previous Face Anti-spoofing (FAS) methods face the challenge of generalizing to unseen domains, mainly because most existing FAS datasets are relatively small and lack data diversity.

Diversity Face Anti-Spoofing +1

Collaboratively Self-supervised Video Representation Learning for Action Recognition

no code implementations15 Jan 2024 Jie Zhang, Zhifan Wan, Lanqing Hu, Stephen Lin, Shuzhe Wu, Shiguang Shan

Considering the close connection between action recognition and human pose estimation, we design a Collaboratively Self-supervised Video Representation (CSVR) learning framework specific to action recognition by jointly factoring in generative pose prediction and discriminative context matching as pretext tasks.

Action Recognition Pose Estimation +2

Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial Robustness

1 code implementation CVPR 2024 Sibo Wang, Jie Zhang, Zheng Yuan, Shiguang Shan

Specifically, PMG-AFT minimizes the distance between the features of adversarial examples in the target model and those in the pre-trained model, aiming to preserve the generalization features already captured by the pre-trained model.

Adversarial Robustness Zero-shot Generalization

Multichannel AV-wav2vec2: A Framework for Learning Multichannel Multi-Modal Speech Representation

1 code implementation7 Jan 2024 Qiushi Zhu, Jie Zhang, Yu Gu, Yuchen Hu, LiRong Dai

Considering that visual information helps to improve speech recognition performance in noisy scenes, in this work we propose a multichannel multi-modal speech self-supervised learning framework AV-wav2vec2, which utilizes video and multichannel audio data as inputs.

Audio-Visual Speech Recognition Automatic Speech Recognition +7

Enhancing RAW-to-sRGB with Decoupled Style Structure in Fourier Domain

1 code implementation4 Jan 2024 Xuanhua He, Tao Hu, Guoli Wang, Zejin Wang, Run Wang, Qian Zhang, Keyu Yan, Ziyi Chen, Rui Li, Chenjun Xie, Jie Zhang, Man Zhou

However, current methods often ignore the difference between cell phone RAW images and DSLR camera RGB images, a difference that goes beyond the color matrix and extends to spatial structure due to resolution variations.

Image Restoration

Frequency-Adaptive Pan-Sharpening with Mixture of Experts

1 code implementation4 Jan 2024 Xuanhua He, Keyu Yan, Rui Li, Chengjun Xie, Jie Zhang, Man Zhou

Pan-sharpening involves reconstructing missing high-frequency information in multi-spectral images with low spatial resolution, using a higher-resolution panchromatic image as guidance.

Mixture-of-Experts

FullLoRA-AT: Efficiently Boosting the Robustness of Pretrained Vision Transformers

no code implementations3 Jan 2024 Zheng Yuan, Jie Zhang, Shiguang Shan

In recent years, the Vision Transformer (ViT) model has gradually become mainstream in various computer vision tasks, and the robustness of the model has received increasing attention.

Adversarial Robustness

Video Harmonization with Triplet Spatio-Temporal Variation Patterns

1 code implementation CVPR 2024 Zonghui Guo, Xinyu Han, Jie Zhang, Shiguang Shan, Haiyong Zheng

Video harmonization is an important and challenging task that aims to obtain visually realistic composite videos by automatically adjusting the foreground's appearance to harmonize with the background.

Triplet Video Enhancement +1

SAME: Sample Reconstruction against Model Extraction Attacks

1 code implementation17 Dec 2023 Yi Xie, Jie Zhang, Shiqian Zhao, Tianwei Zhang, Xiaofeng Chen

While deep learning models have shown significant performance across various domains, their deployment needs extensive resources and advanced computing infrastructure.

model Model extraction

ParsNets: A Parsimonious Orthogonal and Low-Rank Linear Networks for Zero-Shot Learning

no code implementations15 Dec 2023 Jingcai Guo, Qihua Zhou, Ruibing Li, Xiaocheng Lu, Ziming Liu, Junyang Chen, Xin Xie, Jie Zhang

Then, to facilitate the generalization of local linearities, we construct a maximal margin geometry on the learned features by enforcing low-rank constraints on intra-class samples and high-rank constraints on inter-class samples, resulting in orthogonal subspaces for different classes and each subspace lies on a compact manifold.

Zero-Shot Learning

MaTe3D: Mask-guided Text-based 3D-aware Portrait Editing

1 code implementation12 Dec 2023 Kangneng Zhou, Daiheng Gao, Xuan Wang, Jie Zhang, Peng Zhang, Xusen Sun, Longhao Zhang, Shiqi Yang, Bang Zhang, Liefeng Bo, Yaxing Wang, Ming-Ming Cheng

This enhances masked-based editing in local areas; second, we present a novel distillation strategy: Conditional Distillation on Geometry and Texture (CDGT).

Calibration-free quantitative phase imaging in multi-core fiber endoscopes using end-to-end deep learning

no code implementations12 Dec 2023 Jiawei Sun, Bin Zhao, Dong Wang, Zhigang Wang, Jie Zhang, Nektarios Koukourakis, Juergen W. Czarske, Xuelong Li

Quantitative phase imaging (QPI) through multi-core fibers (MCFs) has been an emerging in vivo label-free endoscopic imaging modality with minimal invasiveness.

Retrieval

Control Risk for Potential Misuse of Artificial Intelligence in Science

1 code implementation11 Dec 2023 Jiyan He, Weitao Feng, Yaosen Min, Jingwei Yi, Kunsheng Tang, Shuai Li, Jie Zhang, Kejiang Chen, Wenbo Zhou, Xing Xie, Weiming Zhang, Nenghai Yu, Shuxin Zheng

In this study, we aim to raise awareness of the dangers of AI misuse in science, and call for responsible AI development and use in this domain.

Red Teaming

Data-Free Hard-Label Robustness Stealing Attack

1 code implementation10 Dec 2023 Xiaojian Yuan, Kejiang Chen, Wen Huang, Jie Zhang, Weiming Zhang, Nenghai Yu

In response to these identified gaps, we introduce a novel Data-Free Hard-Label Robustness Stealing (DFHL-RS) attack in this paper, which enables the stealing of both model accuracy and robustness by simply querying hard labels of the target model without the help of any natural data.

Singular Regularization with Information Bottleneck Improves Model's Adversarial Robustness

no code implementations4 Dec 2023 Guanlin Li, Naishan Zheng, Man Zhou, Jie Zhang, Tianwei Zhang

However, these works lack analysis of adversarial information or perturbation, which cannot reveal the mystery of adversarial examples and lose proper interpretation.

Adversarial Robustness

FreePIH: Training-Free Painterly Image Harmonization with Diffusion Model

no code implementations25 Nov 2023 Ruibin Li, Jingcai Guo, Song Guo, Qihua Zhou, Jie Zhang

Specifically, we find that the very last few steps of the denoising (i. e., generation) process strongly correspond to the stylistic information of images, and based on this, we propose to augment the latent features of both the foreground and background images with Gaussians for a direct denoising-based harmonization.

Denoising Image Harmonization +1

Attribute-Aware Representation Rectification for Generalized Zero-Shot Learning

1 code implementation23 Nov 2023 Zhijie Rao, Jingcai Guo, Xiaocheng Lu, Qihua Zhou, Jie Zhang, Kang Wei, Chenxin Li, Song Guo

In this paper, we propose a simple yet effective Attribute-Aware Representation Rectification framework for GZSL, dubbed $\mathbf{(AR)^{2}}$, to adaptively rectify the feature extractor to learn novel features while keeping original valuable features.

Attribute Generalized Zero-Shot Learning +1

Sparsity-Driven EEG Channel Selection for Brain-Assisted Speech Enhancement

no code implementations22 Nov 2023 Jie Zhang, Qing-Tian Xu, Zhen-Hua Ling, Haizhou Li

In this work, we therefore propose a novel end-to-end brain-assisted speech enhancement network (BASEN), which incorporates the listeners' EEG signals and adopts a temporal convolutional network together with a convolutional multi-layer cross attention module to fuse EEG-audio features.

channel selection EEG +1

Improving Adversarial Transferability by Stable Diffusion

no code implementations18 Nov 2023 Jiayang Liu, Siyu Zhu, Siyuan Liang, Jie Zhang, Han Fang, Weiming Zhang, Ee-Chien Chang

Various techniques have emerged to enhance the transferability of adversarial attacks for the black-box scenario.

Segue: Side-information Guided Generative Unlearnable Examples for Facial Privacy Protection in Real World

no code implementations24 Oct 2023 Zhiling Zhang, Jie Zhang, Kui Zhang, Wenbo Zhou, Weiming Zhang, Nenghai Yu

To address these concerns, researchers are actively exploring the concept of ``unlearnable examples", by adding imperceptible perturbation to data in the model training stage, which aims to prevent the model from learning discriminate features of the target face.

Face Recognition

Pix2HDR -- A pixel-wise acquisition and deep learning-based synthesis approach for high-speed HDR videos

no code implementations24 Oct 2023 Caixin Wang, Jie Zhang, Matthew A. Wilson, Ralph Etienne-Cummings

By combining the versatility of pixel-wise sampling patterns with the strength of deep neural networks at decoding complex scenes, our method greatly enhances the vision system's adaptability and performance in dynamic conditions.

IntentDial: An Intent Graph based Multi-Turn Dialogue System with Reasoning Path Visualization

no code implementations18 Oct 2023 Zengguang Hao, Jie Zhang, Binxia Xu, Yafang Wang, Gerard de Melo, Xiaolong Li

Intent detection and identification from multi-turn dialogue has become a widely explored technique in conversational agents, for example, voice assistants and intelligent customer services.

Intent Detection

Real-Fake: Effective Training Data Synthesis Through Distribution Matching

1 code implementation16 Oct 2023 Jianhao Yuan, Jie Zhang, Shuyang Sun, Philip Torr, Bo Zhao

Synthetic training data has gained prominence in numerous learning tasks and scenarios, offering advantages such as dataset augmentation, generalization evaluation, and privacy preservation.

image-classification Image Classification +1

Multiview Transformer: Rethinking Spatial Information in Hyperspectral Image Classification

no code implementations11 Oct 2023 Jie Zhang, Yongshan Zhang, Yicong Zhou

To aggregate the multiview information, a fully-convolutional SED with a U-shape in spectral dimension is introduced to extract a multiview feature map.

Classification Dimensionality Reduction +2

Latent Diffusion Model for Medical Image Standardization and Enhancement

no code implementations8 Oct 2023 Md Selim, Jie Zhang, Faraneh Fathi, Michael A. Brooks, Ge Wang, Guoqiang Yu, Jin Chen

Finally, the decoder uses the transformed latent representation to generate a standardized CT image, providing a more consistent basis for downstream analysis.

Computed Tomography (CT) Decoder +1

Warfare:Breaking the Watermark Protection of AI-Generated Content

1 code implementation27 Sep 2023 Guanlin Li, Yifei Chen, Jie Zhang, Shangwei Guo, Han Qiu, Guoyin Wang, Jiwei Li, Tianwei Zhang

AI-Generated Content (AIGC) is rapidly expanding, with services using advanced generative models to create realistic images and fluent text.

Generative Adversarial Network

Cluster-based Method for Eavesdropping Identification and Localization in Optical Links

no code implementations25 Sep 2023 Haokun Song, Rui Lin, Andrea Sgambelluri, Filippo Cugini, Yajie Li, Jie Zhang, Paolo Monti

We propose a cluster-based method to detect and locate eavesdropping events in optical line systems characterized by small power losses.

Understanding Data Augmentation from a Robustness Perspective

no code implementations7 Sep 2023 Zhendong Liu, Jie Zhang, Qiangqiang He, Chongjun Wang

In the realm of visual recognition, data augmentation stands out as a pivotal technique to amplify model robustness.

Data Augmentation

Rep2wav: Noise Robust text-to-speech Using self-supervised representations

no code implementations28 Aug 2023 Qiushi Zhu, Yu Gu, Rilin Chen, Chao Weng, Yuchen Hu, LiRong Dai, Jie Zhang

Noise-robust TTS models are often trained using the enhanced speech, which thus suffer from speech distortion and background noise that affect the quality of the synthesized speech.

Speech Enhancement text-to-speech +1

Backdooring Textual Inversion for Concept Censorship

no code implementations21 Aug 2023 Yutong Wu, Jie Zhang, Florian Kerschbaum, Tianwei Zhang

Users can easily download the word embedding from public websites like Civitai and add it to their own stable diffusion model without fine-tuning for personalization.

Patch Is Not All You Need

no code implementations21 Aug 2023 Changzhen Li, Jie Zhang, Yang Wei, Zhilong Ji, Jinfeng Bai, Shiguang Shan

Vision Transformers have achieved great success in computer visions, delivering exceptional performance across various tasks.

All

Semantic-Human: Neural Rendering of Humans from Monocular Video with Human Parsing

no code implementations19 Aug 2023 Jie Zhang, Pengcheng Shi, Zaiwang Gu, Yiyang Zhou, Zhi Wang

In this paper, we present Semantic-Human, a novel method that achieves both photorealistic details and viewpoint-consistent human parsing for the neural rendering of humans.

Denoising Human Parsing +3

Overlap Bias Matching is Necessary for Point Cloud Registration

no code implementations18 Aug 2023 Pengcheng Shi, Jie Zhang, Haozhe Cheng, Junyang Wang, Yiyang Zhou, Chenlin Zhao, Jihua Zhu

Specifically, we propose a plug-and-play Overlap Bias Matching Module (OBMM) comprising two integral components, overlap sampling module and bias prediction module.

Point Cloud Registration

Mobile Supply: The Last Piece of Jigsaw of Recommender System

no code implementations7 Aug 2023 Zhenhao Jiang, Biao Zeng, Hao Feng, Jin Liu, Jie Zhang, Jia Jia, Ning Hu

In order to address the problem of pagination trigger mechanism, we propose a completely new module in the pipeline of recommender system named Mobile Supply.

Recommendation Systems Re-Ranking

Sampling to Distill: Knowledge Transfer from Open-World Data

no code implementations31 Jul 2023 Yuzheng Wang, Zhaoyu Chen, Jie Zhang, Dingkang Yang, Zuhao Ge, Yang Liu, Siao Liu, Yunquan Sun, Wenqiang Zhang, Lizhe Qi

Data-Free Knowledge Distillation (DFKD) is a novel task that aims to train high-performance student models using only the pre-trained teacher network without original training data.

Data-free Knowledge Distillation Transfer Learning

Rethinking Data Distillation: Do Not Overlook Calibration

1 code implementation ICCV 2023 Dongyao Zhu, Bowen Lei, Jie Zhang, Yanbo Fang, Ruqi Zhang, Yiqun Xie, Dongkuan Xu

Neural networks trained on distilled data often produce over-confident output and require correction by calibration methods.

Dataset Distillation

Enhancing Job Recommendation through LLM-based Generative Adversarial Networks

no code implementations20 Jul 2023 Yingpeng Du, Di Luo, Rui Yan, Hongzhi Liu, Yang song, HengShu Zhu, Jie Zhang

However, directly leveraging LLMs to enhance recommendation results is not a one-size-fits-all solution, as LLMs may suffer from fabricated generation and few-shot problems, which degrade the quality of resume completion.

Our Model Achieves Excellent Performance on MovieLens: What Does it Mean?

1 code implementation19 Jul 2023 Yu-chen Fan, Yitong Ji, Jie Zhang, Aixin Sun

First, there are significant differences in user interactions at the different stages when a user interacts with the MovieLens platform.

Recommendation Systems

ESMC: Entire Space Multi-Task Model for Post-Click Conversion Rate via Parameter Constraint

no code implementations18 Jul 2023 Zhenhao Jiang, Biao Zeng, Hao Feng, Jin Liu, Jicong Fan, Jie Zhang, Jia Jia, Ning Hu, Xingyu Chen, Xuguang Lan

We propose a novel Entire Space Multi-Task Model for Post-Click Conversion Rate via Parameter Constraint (ESMC) and two alternatives: Entire Space Multi-Task Model with Siamese Network (ESMS) and Entire Space Multi-Task Model in Global Domain (ESMG) to address the PSC issue.

Decision Making Recommendation Systems +1

Learning Subjective Time-Series Data via Utopia Label Distribution Approximation

no code implementations15 Jul 2023 Wenxin Xu, Hexin Jiang, Xuefeng Liang, Ying Zhou, Yin Zhao, Jie Zhang

In this work, we propose Utopia Label Distribution Approximation (ULDA) for time-series data, which makes the training label distribution closer to real-world but unknown (utopia) label distribution.

Age Estimation Depth Estimation +4

Using electrical impedance spectroscopy to identify equivalent circuit models of lubricated contacts with complex geometry: in-situ application to mini traction machine

no code implementations7 Jul 2023 Min Yu, Jie Zhang, Arndt Joedicke, Tom Reddyhoff

Overall, the proposed method is applicable to general lubricated interfaces for the identification of equivalent circuit models, which in turn facilitates in-situ tribo-contacts with electric impedance measurement of oil film thickness.

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