Search Results for author: Qing Li

Found 306 papers, 116 papers with code

Collaborative Learning of Bidirectional Decoders for Unsupervised Text Style Transfer

1 code implementation EMNLP 2021 Yun Ma, Yangbin Chen, Xudong Mao, Qing Li

In this paper, we propose a collaborative learning framework for unsupervised text style transfer using a pair of bidirectional decoders, one decoding from left to right while the other decoding from right to left.

Attribute Decoder +4

Exploring Non-Autoregressive Text Style Transfer

1 code implementation EMNLP 2021 Yun Ma, Qing Li

In this paper, we explore Non-AutoRegressive (NAR) decoding for unsupervised text style transfer.

Contrastive Learning Knowledge Distillation +3

Conditional Causal Relationships between Emotions and Causes in Texts

no code implementations EMNLP 2020 Xinhong Chen, Qing Li, JianPing Wang

The causal relationships between emotions and causes in text have recently received a lot of attention.

valid

Task-oriented Domain-specific Meta-Embedding for Text Classification

no code implementations EMNLP 2020 Xin Wu, Yi Cai, Yang Kai, Tao Wang, Qing Li

Meta-embedding learning, which combines complementary information in different word embeddings, have shown superior performances across different Natural Language Processing tasks.

General Classification text-classification +2

Reliable Reasoning Path: Distilling Effective Guidance for LLM Reasoning with Knowledge Graphs

no code implementations12 Jun 2025 Yilin Xiao, Chuang Zhou, Qinggang Zhang, Bo Li, Qing Li, Xiao Huang

Large language models (LLMs) often struggle with knowledge-intensive tasks due to a lack of background knowledge and a tendency to hallucinate.

Knowledge Graphs

LEO-VL: Towards 3D Vision-Language Generalists via Data Scaling with Efficient Representation

no code implementations11 Jun 2025 Jiangyong Huang, Xiaojian Ma, Xiongkun Linghu, Yue Fan, Junchao He, Wenxin Tan, Qing Li, Song-Chun Zhu, Yixin Chen, Baoxiong Jia, Siyuan Huang

A key obstacle to developing 3D-VL generalists lies in data scalability, hindered by the lack of an efficient scene representation.

CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval

no code implementations31 May 2025 Jiahui Geng, Fengyu Cai, Shaobo Cui, Qing Li, LiangWei Chen, Chenyang Lyu, Haonan Li, Derui Zhu, Walter Pretschner, Heinz Koeppl, Fakhri Karray

Using CoQuIR, we benchmark 23 retrieval models, covering both open-source and proprietary systems, and find that even top-performing models frequently fail to distinguish buggy or insecure code from their more robust counterparts.

Code Generation Information Retrieval +1

When Large Multimodal Models Confront Evolving Knowledge:Challenges and Pathways

1 code implementation30 May 2025 Kailin Jiang, Yuntao Du, Yukai Ding, Yuchen Ren, Ning Jiang, Zhi Gao, Zilong Zheng, Lei Liu, Bin Li, Qing Li

Previous work focused on constructing textual knowledge datasets and exploring knowledge injection in LLMs, lacking exploration of multimodal evolving knowledge injection in LMMs.

Continual Learning Image Augmentation +1

Infi-MMR: Curriculum-based Unlocking Multimodal Reasoning via Phased Reinforcement Learning in Multimodal Small Language Models

no code implementations29 May 2025 Zeyu Liu, Yuhang Liu, Guanghao Zhu, Congkai Xie, Zhen Li, Jianbo Yuan, Xinyao Wang, Qing Li, Shing-Chi Cheung, Shengyu Zhang, Fei Wu, Hongxia Yang

Recent advancements in large language models (LLMs) have demonstrated substantial progress in reasoning capabilities, such as DeepSeek-R1, which leverages rule-based reinforcement learning to enhance logical reasoning significantly.

Logical Reasoning Math +1

VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration

1 code implementation26 May 2025 Jiahui Geng, Qing Li, Zongxiong Chen, Yuxia Wang, Derui Zhu, Zhuohan Xie, Chenyang Lyu, Xiuying Chen, Preslav Nakov, Fakhri Karray

In this paper, we introduce the concept of $\textit{safety calibration}$, which systematically addresses both undersafety and oversafety.

Language Modeling Language Modelling +1

Removal of Hallucination on Hallucination: Debate-Augmented RAG

1 code implementation24 May 2025 Wentao Hu, WengYu Zhang, Yiyang Jiang, Chen Jason Zhang, XiaoYong Wei, Qing Li

Retrieval-Augmented Generation (RAG) enhances factual accuracy by integrating external knowledge, yet it introduces a critical issue: erroneous or biased retrieval can mislead generation, compounding hallucinations, a phenomenon we term Hallucination on Hallucination.

Hallucination RAG +2

EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models

no code implementations24 May 2025 Guanghao Meng, Sunan He, Jinpeng Wang, Tao Dai, Letian Zhang, Jieming Zhu, Qing Li, Gang Wang, Rui Zhang, Yong Jiang

To address this problem, we propose the Entity Visual Description enhanced CLIP (EvdCLIP), designed to leverage the visual knowledge of entities to enrich queries.

Image-text Retrieval Language Modeling +3

Distributed Expectation Propagation for Multi-Object Tracking over Sensor Networks

no code implementations24 May 2025 Qing Li, Runze Gan, James R. Hopgood, Michael E. Davies, Simon J. Godsill

In this paper, we present a novel distributed expectation propagation algorithm for multiple sensors, multiple objects tracking in cluttered environments.

Multi-Object Tracking

MGStream: Motion-aware 3D Gaussian for Streamable Dynamic Scene Reconstruction

1 code implementation20 May 2025 Zhenyu Bao, Qing Li, Guibiao Liao, Zhongyuan Zhao, Kanglin Liu

The rigid deformation is applied to the motion-related 3DGs for modeling the dynamic, and the attention-based optimization on the motion-related 3DGs enables the reconstruction of the emerging objects.

3DGS Computational Efficiency +1

MSDformer: Multi-scale Discrete Transformer For Time Series Generation

no code implementations20 May 2025 Zhicheng Chen, Shibo Feng, Xi Xiao, Zhong Zhang, Qing Li, Xingyu Gao, Peilin Zhao

MSDformer employs a multi-scale time series tokenizer to learn discrete token representations at multiple scales, which jointly characterize the complex nature of time series data.

Model Optimization Time Series +1

GLProtein: Global-and-Local Structure Aware Protein Representation Learning

no code implementations17 May 2025 Yunqing Liu, Wenqi Fan, XiaoYong Wei, Qing Li

We argue that the structural information of proteins is not only limited to their 3D information but also encompasses information from amino acid molecules (local information) to protein-protein structure similarity (global information).

Representation Learning Triplet

FlowDreamer: A RGB-D World Model with Flow-based Motion Representations for Robot Manipulation

no code implementations15 May 2025 Jun Guo, Xiaojian Ma, Yikai Wang, Min Yang, Huaping Liu, Qing Li

This paper investigates training better visual world models for robot manipulation, i. e., models that can predict future visual observations by conditioning on past frames and robot actions.

Robot Manipulation Semantic Similarity +2

Seeing Beyond the Scene: Enhancing Vision-Language Models with Interactional Reasoning

no code implementations14 May 2025 Dayong Liang, Changmeng Zheng, Zhiyuan Wen, Yi Cai, Xiao-Yong Wei, Qing Li

Traditional scene graphs primarily focus on spatial relationships, limiting vision-language models' (VLMs) ability to reason about complex interactions in visual scenes.

Relation Extraction Scene Understanding

Emotion-Qwen: Training Hybrid Experts for Unified Emotion and General Vision-Language Understanding

1 code implementation10 May 2025 Dawei Huang, Qing Li, Chuan Yan, Zebang Cheng, Yurong Huang, Xiang Li, Bin Li, Xiaohui Wang, Zheng Lian, Xiaojiang Peng

While Large Multimodal Models (LMMs) have demonstrated significant progress in general vision-language (VL) tasks, their performance in emotion-specific scenarios remains limited.

Descriptive Emotion Recognition +1

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

TongUI: Building Generalized GUI Agents by Learning from Multimodal Web Tutorials

1 code implementation17 Apr 2025 Bofei Zhang, Zirui Shang, Zhi Gao, Wang Zhang, Rui Xie, Xiaojian Ma, Tao Yuan, Xinxiao wu, Song-Chun Zhu, Qing Li

Building Graphical User Interface (GUI) agents is a promising research direction, which simulates human interaction with computers or mobile phones to perform diverse GUI tasks.

Articles

SemDiff: Generating Natural Unrestricted Adversarial Examples via Semantic Attributes Optimization in Diffusion Models

no code implementations16 Apr 2025 Zeyu Dai, Shengcai Liu, Rui He, Jiahao Wu, Ning Lu, Wenqi Fan, Qing Li, Ke Tang

In light of this, we propose SemDiff, a novel unrestricted adversarial attack that explores the semantic latent space of diffusion models for meaningful attributes, and devises a multi-attributes optimization approach to ensure attack success while maintaining the naturalness and imperceptibility of generated UAEs.

Adversarial Attack

Exploring Backdoor Attack and Defense for LLM-empowered Recommendations

no code implementations15 Apr 2025 Liangbo Ning, Wenqi Fan, Qing Li

Specifically, we introduce an LLM-based poison scanner to detect the poisoned items by leveraging the powerful language understanding and rich knowledge of LLMs.

Backdoor Attack Recommendation Systems

CheatAgent: Attacking LLM-Empowered Recommender Systems via LLM Agent

no code implementations13 Apr 2025 Liang-bo Ning, Shijie Wang, Wenqi Fan, Qing Li, Xin Xu, Hao Chen, Feiran Huang

Recently, Large Language Model (LLM)-empowered recommender systems (RecSys) have brought significant advances in personalized user experience and have attracted considerable attention.

Large Language Model Recommendation Systems +1

Investigating and Mitigating Stereotype-aware Unfairness in LLM-based Recommendations

no code implementations5 Apr 2025 Zihuai Zhao, Wenqi Fan, Yao Wu, Qing Li

Large Language Models (LLMs) have demonstrated unprecedented language understanding and reasoning capabilities to capture diverse user preferences and advance personalized recommendations.

Fairness Recommendation Systems +1

Retrieval-Augmented Purifier for Robust LLM-Empowered Recommendation

no code implementations3 Apr 2025 Liangbo Ning, Wenqi Fan, Qing Li

Recently, Large Language Model (LLM)-empowered recommender systems have revolutionized personalized recommendation frameworks and attracted extensive attention.

RAG Recommendation Systems +2

Unveiling the Mist over 3D Vision-Language Understanding: Object-centric Evaluation with Chain-of-Analysis

1 code implementation CVPR 2025 Jiangyong Huang, Baoxiong Jia, Yan Wang, Ziyu Zhu, Xiongkun Linghu, Qing Li, Song-Chun Zhu, Siyuan Huang

Our evaluation of state-of-the-art 3D-VL models on Beacon3D reveals that (i) object-centric evaluation elicits true model performance and particularly weak generalization in QA; (ii) grounding-QA coherence remains fragile in current 3D-VL models, and (iii) incorporating large language models (LLMs) to 3D-VL models, though as a prevalent practice, hinders grounding capabilities and has yet to elevate QA capabilities.

3D Question Answering (3D-QA) 3D visual grounding

SPC-GS: Gaussian Splatting with Semantic-Prompt Consistency for Indoor Open-World Free-view Synthesis from Sparse Inputs

no code implementations CVPR 2025 Guibiao Liao, Qing Li, Zhenyu Bao, Guoping Qiu, Kanglin Liu

However, they exhibit poor performance when confronted with sparse inputs, primarily due to the sparse distribution of Gaussian points and insufficient view supervision.

Semantic Segmentation Video Generation

SAUCE: Selective Concept Unlearning in Vision-Language Models with Sparse Autoencoders

no code implementations16 Mar 2025 Qing Li, Jiahui Geng, Derui Zhu, Fengyu Cai, Chenyang Lyu, Fakhri Karray

To address this issue, we introduce SAUCE, a novel method that leverages sparse autoencoders (SAEs) for fine-grained and selective concept unlearning in VLMs.

ConsisLoRA: Enhancing Content and Style Consistency for LoRA-based Style Transfer

no code implementations13 Mar 2025 Bolin Chen, Baoquan Zhao, Haoran Xie, Yi Cai, Qing Li, Xudong Mao

In this paper, we comprehensively analyze the limitations of the standard diffusion parameterization, which learns to predict noise, in the context of style transfer.

continuous-control Continuous Control +1

Towards Next-Generation Recommender Systems: A Benchmark for Personalized Recommendation Assistant with LLMs

1 code implementation12 Mar 2025 Jiani Huang, Shijie Wang, Liang-bo Ning, Wenqi Fan, Shuaiqiang Wang, Dawei Yin, Qing Li

To address this gap, we introduce RecBench+, a new dataset benchmark designed to access LLMs' ability to handle intricate user recommendation needs in the era of LLMs.

Recommendation Systems

Brain Inspired Adaptive Memory Dual-Net for Few-Shot Image Classification

no code implementations10 Mar 2025 Kexin Di, Xiuxing Li, Yuyang Han, Ziyu Li, Qing Li, Xia Wu

Few-shot image classification has become a popular research topic for its wide application in real-world scenarios, however the problem of supervision collapse induced by single image-level annotation remains a major challenge.

Few-Shot Image Classification Hippocampus +1

Bridging the Vision-Brain Gap with an Uncertainty-Aware Blur Prior

1 code implementation CVPR 2025 Haitao Wu, Qing Li, Changqing Zhang, Zhen He, Xiaomin Ying

When encoded brain representations are directly aligned with the corresponding pretrained image features, the System GAP and Random GAP between paired data challenge the model, requiring it to bridge these gaps.

Image Retrieval

Towards Universal Learning-based Model for Cardiac Image Reconstruction: Summary of the CMRxRecon2024 Challenge

1 code implementation5 Mar 2025 Fanwen Wang, Zi Wang, Yan Li, Jun Lyu, Chen Qin, Shuo Wang, Kunyuan Guo, Mengting Sun, Mingkai Huang, Haoyu Zhang, Michael Tänzer, Qirong Li, Xinran Chen, Jiahao Huang, Yinzhe Wu, Kian Anvari Hamedani, Yuntong Lyu, Longyu Sun, Qing Li, Ziqiang Xu, Bingyu Xin, Dimitris N. Metaxas, Narges Razizadeh, Shahabedin Nabavi, George Yiasemis, Jonas Teuwen, Zhenxi Zhang, Sha Wang, Chi Zhang, Daniel B. Ennis, Zhihao Xue, Chenxi Hu, Ruru Xu, Ilkay Oksuz, Donghang Lyu, Yanxin Huang, Xinrui Guo, Ruqian Hao, Jaykumar H. Patel, Guanke Cai, Binghua Chen, Yajing Zhang, Sha Hua, Zhensen Chen, Qi Dou, Xiahai Zhuang, Qian Tao, Wenjia Bai, Jing Qin, He Wang, Claudia Prieto, Michael Markl, Alistair Young, Hao Li, Xihong Hu, Lianmin Wu, Xiaobo Qu, Guang Yang, Chengyan Wang

In addition, through a detailed analysis of the results submitted to the challenge, we have also made several findings, including: 1) adaptive prompt-learning embedding is an effective means for achieving strong generalization in reconstruction models; 2) enhanced data consistency based on physics-informed networks is also an effective pathway toward a universal model; 3) traditional evaluation metrics have limitations when assessing ground-truth references with moderate or lower image quality, highlighting the need for subjective evaluation methods.

Benchmarking Image Reconstruction +3

Calibrating LLM Confidence with Semantic Steering: A Multi-Prompt Aggregation Framework

no code implementations4 Mar 2025 Ziang Zhou, Tianyuan Jin, Jieming Shi, Qing Li

Large Language Models (LLMs) often exhibit misaligned confidence scores, usually overestimating the reliability of their predictions.

Artificial Intelligence in Reactor Physics: Current Status and Future Prospects

no code implementations4 Mar 2025 Ruizhi Zhang, Shengfeng Zhu, Kan Wang, Ding She, Jean-Philippe Argaud, Bertrand Bouriquet, Qing Li, Helin Gong

Reactor physics is the study of neutron properties, focusing on using models to examine the interactions between neutrons and materials in nuclear reactors.

Parameter Prediction

MMKE-Bench: A Multimodal Editing Benchmark for Diverse Visual Knowledge

1 code implementation27 Feb 2025 Yuntao Du, Kailin Jiang, Zhi Gao, Chenrui Shi, Zilong Zheng, Siyuan Qi, Qing Li

Knowledge editing techniques have emerged as essential tools for updating the factual knowledge of large language models (LLMs) and multimodal models (LMMs), allowing them to correct outdated or inaccurate information without retraining from scratch.

knowledge editing

HyperG: Hypergraph-Enhanced LLMs for Structured Knowledge

no code implementations25 Feb 2025 Sirui Huang, Hanqian Li, Yanggan Gu, Xuming Hu, Qing Li, Guandong Xu

Given that substantial amounts of domain-specific knowledge are stored in structured formats, such as web data organized through HTML, Large Language Models (LLMs) are expected to fully comprehend this structured information to broaden their applications in various real-world downstream tasks.

FedORGP: Guiding Heterogeneous Federated Learning with Orthogonality Regularization on Global Prototypes

no code implementations22 Feb 2025 Fucheng Guo, Zeyu Luan, Qing Li, Dan Zhao, Yong Jiang

Federated Learning (FL) has emerged as an essential framework for distributed machine learning, especially with its potential for privacy-preserving data processing.

Federated Learning Privacy Preserving

A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

no code implementations22 Feb 2025 Jiahui Geng, Qing Li, Herbert Woisetschlaeger, Zongxiong Chen, Yuxia Wang, Preslav Nakov, Hans-Arno Jacobsen, Fakhri Karray

This study investigates the machine unlearning techniques within the context of large language models (LLMs), referred to as \textit{LLM unlearning}.

Machine Unlearning

Cardiac Evidence Backtracking for Eating Behavior Monitoring using Collocative Electrocardiogram Imagining

no code implementations20 Feb 2025 Xu-Lu Zhang, Zhen-Qun Yang, Dong-Mei Jiang, Ga Liao, Qing Li, Ramesh Jain, Xiao-Yong Wei

This is accomplished using a collocative learning framework in which 1) we construct collocative tensors as pseudo-images from 1D ECG signals to improve the feasibility of 2D image-based deep models; 2) we formulate the cardiac logic of analyzing the ECG data in a comparative way as periodic attention regulators so as to guide the deep inference to collect evidence in a human comprehensible manner; and 3) we improve the interpretability of the framework by enabling the backtracking of evidence with a set of methods designed for Class Activation Mapping (CAM) decoding and decision tree/forest generation.

Utilizing Effective Dynamic Graph Learning to Shield Financial Stability from Risk Propagation

no code implementations18 Feb 2025 Guanyuan Yu, Qing Li, Yu Zhao, Jun Wang, Yijun Chen, Shaolei Chen

Our approach represents a significant advancement in leveraging artificial intelligence to enhance financial stability, offering a powerful solution to mitigate the spread of risks within financial networks.

Graph Learning

Knapsack Optimization-based Schema Linking for LLM-based Text-to-SQL Generation

no code implementations18 Feb 2025 Zheng Yuan, Hao Chen, Zijin Hong, Qinggang Zhang, Feiran Huang, Qing Li, Xiao Huang

Extensive experiments on Spider and BIRD benchmarks verify that KaSLA can significantly improve the SQL generation performance of SOTA Text2SQL models by substituting their schema linking processes.

Text to SQL Text-To-SQL

Exposing Numeracy Gaps: A Benchmark to Evaluate Fundamental Numerical Abilities in Large Language Models

1 code implementation16 Feb 2025 Haoyang Li, Xuejia Chen, Zhanchao Xu, Darian Li, Nicole Hu, Fei Teng, Yiming Li, Luyu Qiu, Chen Jason Zhang, Qing Li, Lei Chen

Large Language Models (LLMs) have demonstrated impressive capabilities in natural language processing tasks, such as text generation and semantic understanding.

Language Modeling Language Modelling +4

Generating on Generated: An Approach Towards Self-Evolving Diffusion Models

no code implementations14 Feb 2025 Xulu Zhang, XiaoYong Wei, Jinlin Wu, Jiaxin Wu, Zhaoxiang Zhang, Zhen Lei, Qing Li

Recursive Self-Improvement (RSI) enables intelligence systems to autonomously refine their capabilities.

QueryAttack: Jailbreaking Aligned Large Language Models Using Structured Non-natural Query Language

1 code implementation13 Feb 2025 Qingsong Zou, Jingyu Xiao, Qing Li, Zhi Yan, Yuhang Wang, Li Xu, Wenxuan Wang, Kuofeng Gao, Ruoyu Li, Yong Jiang

By treating LLMs as knowledge databases, we translate malicious queries in natural language into structured non-natural query language to bypass the safety alignment mechanisms of LLMs.

Safety Alignment

Randomness of Low-Layer Parameters Determines Confusing Samples in Terms of Interaction Representations of a DNN

no code implementations12 Feb 2025 Junpeng Zhang, Lei Cheng, Qing Li, Liang Lin, Quanshi Zhang

In this paper, we find that the complexity of interactions encoded by a deep neural network (DNN) can explain its generalization power.

AutoGUI: Scaling GUI Grounding with Automatic Functionality Annotations from LLMs

no code implementations4 Feb 2025 Hongxin Li, Jingfan Chen, Jingran Su, Yuntao Chen, Qing Li, Zhaoxiang Zhang

In this work, we propose the \methodname{} pipeline for automatically annotating UI elements with detailed functionality descriptions at scale.

Can You Move These Over There? An LLM-based VR Mover for Supporting Object Manipulation

no code implementations4 Feb 2025 Xiangzhi Eric Wang, Zackary P. T. Sin, Ye Jia, Daniel Archer, Wynonna H. Y. Fong, Qing Li, Chen Li

In our daily lives, we can naturally convey instructions for the spatial manipulation of objects using words and gestures.

Object

Synthetic User Behavior Sequence Generation with Large Language Models for Smart Homes

no code implementations31 Jan 2025 Zhiyao Xu, Dan Zhao, Qingsong Zou, Jingyu Xiao, Yong Jiang, Zhenhui Yuan, Qing Li

In this paper, we propose an LLM-based synthetic dataset generation IoTGen framework to enhance the generalization of downstream smart home intelligent models.

Anomaly Detection Dataset Generation

STAR: Stepwise Task Augmentation and Relation Learning for Aspect Sentiment Quad Prediction

no code implementations27 Jan 2025 Wenna Lai, Haoran Xie, Guandong Xu, Qing Li

The most challenging task, aspect sentiment quad prediction (ASQP), predicts these elements simultaneously, hindered by difficulties in accurately coupling different sentiment elements.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2

Internal Activation Revision: Safeguarding Vision Language Models Without Parameter Update

no code implementations24 Jan 2025 Qing Li, Jiahui Geng, Zongxiong Chen, Kun Song, Lei Ma, Fakhri Karray

Vision-language models (VLMs) demonstrate strong multimodal capabilities but have been found to be more susceptible to generating harmful content compared to their backbone large language models (LLMs).

Computational Protein Science in the Era of Large Language Models (LLMs)

no code implementations17 Jan 2025 Wenqi Fan, Yi Zhou, Shijie Wang, Yuyao Yan, Hui Liu, Qian Zhao, Le Song, Qing Li

As a result, researchers have actively introduced LLM techniques in computational protein science, developing protein Language Models (pLMs) that skillfully grasp the foundational knowledge of proteins and can be effectively generalized to solve a diversity of sequence-structure-function reasoning problems.

Drug Discovery Protein Design +2

LongViTU: Instruction Tuning for Long-Form Video Understanding

no code implementations9 Jan 2025 Rujie Wu, Xiaojian Ma, Hai Ci, Yue Fan, Yuxuan Wang, Haozhe Zhao, Qing Li, Yizhou Wang

Each QA pair in LongViTU features: 1) long-term context (average certificate length of 4. 6 minutes); 2) rich knowledge and condensed reasoning (commonsense, causality, planning, etc.)).

EgoSchema Form +2

Efficient Graph Condensation via Gaussian Process

1 code implementation5 Jan 2025 Lin Wang, Qing Li

To address these issues, this paper proposes Graph Condensation via Gaussian Process (GCGP), a novel and computationally efficient approach to graph condensation.

Contrastive Learning Augmented Social Recommendations

1 code implementation3 Jan 2025 Lin Wang, Weisong Wang, Xuanji Xiao, Qing Li

To mitigate noise propagation in graph data and extract reliable social interests, we introduce a dual-view denoising framework.

Contrastive Learning Denoising +2

Revisiting Graph Neural Networks on Graph-level Tasks: Comprehensive Experiments, Analysis, and Improvements

no code implementations1 Jan 2025 Haoyang Li, Yuming Xu, Chen Jason Zhang, Alexander Zhou, Lei Chen, Qing Li

Graph-level tasks, which predict properties or classes for the entire graph, are critical for applications, such as molecular property prediction and subgraph counting.

Contrastive Learning Graph Classification +3

Embodied VideoAgent: Persistent Memory from Egocentric Videos and Embodied Sensors Enables Dynamic Scene Understanding

no code implementations31 Dec 2024 Yue Fan, Xiaojian Ma, Rongpeng Su, Jun Guo, Rujie Wu, Xi Chen, Qing Li

This paper investigates the problem of understanding dynamic 3D scenes from egocentric observations, a key challenge in robotics and embodied AI.

Robot Manipulation Scene Understanding +1

A Survey on Large Language Model Acceleration based on KV Cache Management

1 code implementation27 Dec 2024 Haoyang Li, Yiming Li, Anxin Tian, Tianhao Tang, Zhanchao Xu, Xuejia Chen, Nicole Hu, Wei Dong, Qing Li, Lei Chen

This survey provides a comprehensive overview of KV cache management strategies for LLM acceleration, categorizing them into token-level, model-level, and system-level optimizations.

Language Modeling Language Modelling +5

Multi-modal Agent Tuning: Building a VLM-Driven Agent for Efficient Tool Usage

no code implementations20 Dec 2024 Zhi Gao, Bofei Zhang, Pengxiang Li, Xiaojian Ma, Tao Yuan, Yue Fan, Yuwei Wu, Yunde Jia, Song-Chun Zhu, Qing Li

The advancement of large language models (LLMs) prompts the development of multi-modal agents, which are used as a controller to call external tools, providing a feasible way to solve practical tasks.

Language Modeling Language Modelling

PolySmart @ TRECVid 2024 Video Captioning (VTT)

no code implementations20 Dec 2024 Jiaxin Wu, WengYu Zhang, Xiao-Yong Wei, Qing Li

In this paper, we present our methods and results for the Video-To-Text (VTT) task at TRECVid 2024, exploring the capabilities of Vision-Language Models (VLMs) like LLaVA and LLaVA-NeXT-Video in generating natural language descriptions for video content.

Video Captioning

PolySmart @ TRECVid 2024 Medical Video Question Answering

no code implementations20 Dec 2024 Jiaxin Wu, Yiyang Jiang, Xiao-Yong Wei, Qing Li

Specifically, we provide the video captions generated by the LLaVA-Next-Video model and the video subtitles with timestamps as context, and ask GPT4 to generate step captions for the given medical query.

Question Answering Text Retrieval +2

Score-based Generative Diffusion Models for Social Recommendations

1 code implementation20 Dec 2024 Chengyi Liu, Jiahao Zhang, Shijie Wang, Wenqi Fan, Qing Li

With the prevalence of social networks on online platforms, social recommendation has become a vital technique for enhancing personalized recommendations.

Self-Supervised Learning

TOMG-Bench: Evaluating LLMs on Text-based Open Molecule Generation

1 code implementation19 Dec 2024 Jiatong Li, Junxian Li, Yunqing Liu, Dongzhan Zhou, Qing Li

In this paper, we propose Text-based Open Molecule Generation Benchmark (TOMG-Bench), the first benchmark to evaluate the open-domain molecule generation capability of LLMs.

Benchmarking Description-guided molecule generation

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation

no code implementations15 Dec 2024 Ziang Zhou, Zhihao Ding, Jieming Shi, Qing Li, Shiqi Shen

In this paper, we present TINED, a novel approach that distills GNNs to MLPs on a layer-by-layer basis using Teacher Injection and Dirichlet Energy Distillation techniques.

Node Classification

Learning to Correction: Explainable Feedback Generation for Visual Commonsense Reasoning Distractor

1 code implementation8 Dec 2024 Jiali Chen, Xusen Hei, Yuqi Xue, Yuancheng Wei, Jiayuan Xie, Yi Cai, Qing Li

Large multimodal models (LMMs) have shown remarkable performance in the visual commonsense reasoning (VCR) task, which aims to answer a multiple-choice question based on visual commonsense within an image.

Misconceptions Multiple-choice +1

MolReFlect: Towards Fine-grained In-Context Alignment between Molecules and Texts

no code implementations arXiv preprint 2024 Jiatong Li, Yunqing Liu, Wei Liu, Jingdi Lei, Di Zhang, Wenqi Fan, Dongzhan Zhou, Yuqiang Li, Qing Li

Previous endeavours often treat the molecule as a general SMILES string or molecular graph, neglecting the fine-grained alignments between the molecular sub-structures and the descriptive textual phrases, which are crucial for accurate and explainable predictions.

Descriptive Molecule Captioning +1

MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts

no code implementations22 Nov 2024 Jiatong Li, Yunqing Liu, Wei Liu, Jingdi Le, Di Zhang, Wenqi Fan, Dongzhan Zhou, Yuqiang Li, Qing Li

Previous endeavours often treat the molecule as a general SMILES string or molecular graph, neglecting the fine-grained alignments between the molecular sub-structures and the descriptive textual phrases, which are crucial for accurate and explainable predictions.

Descriptive

Efficient and Robust Regularized Federated Recommendation

1 code implementation3 Nov 2024 Langming Liu, Wanyu Wang, Xiangyu Zhao, Zijian Zhang, Chunxu Zhang, Shanru Lin, Yiqi Wang, Lixin Zou, Zitao Liu, Xuetao Wei, Hongzhi Yin, Qing Li

In user preference modeling, both methods learn local and global models, collaboratively learning users' common and personalized interests under the federated learning setting.

Federated Learning Recommendation Systems

Enhance Hyperbolic Representation Learning via Second-order Pooling

no code implementations29 Oct 2024 Kun Song, Ruben Solozabal, Li Hao, Lu Ren, Moloud Abdar, Qing Li, Fakhri Karray, Martin Takac

To address this issue, we introduce second-order pooling into hyperbolic representation learning, as it naturally increases the distance between samples without compromising the generalization ability of the input features.

Representation Learning

DMVC: Multi-Camera Video Compression Network aimed at Improving Deep Learning Accuracy

no code implementations24 Oct 2024 Huan Cui, Qing Li, Hanling Wang, Yong Jiang

We introduce a cutting-edge video compression framework tailored for the age of ubiquitous video data, uniquely designed to serve machine learning applications.

Data Compression Video Compression

Schrodinger's Memory: Large Language Models

no code implementations16 Sep 2024 Wei Wang, Qing Li

So, what is the underlying mechanism of this memory?

Autonomous Vehicle Decision-Making Framework for Considering Malicious Behavior at Unsignalized Intersections

no code implementations11 Sep 2024 Qing Li, Jinxing Hua, Qiuxia Sun

In this paper, we propose a Q-learning based decision-making framework to improve the safety and efficiency of Autonomous Vehicles when they encounter other maliciously behaving vehicles while passing through unsignalized intersections.

Autonomous Vehicles Decision Making +1

LATEX-GCL: Large Language Models (LLMs)-Based Data Augmentation for Text-Attributed Graph Contrastive Learning

no code implementations2 Sep 2024 Haoran Yang, Xiangyu Zhao, Sirui Huang, Qing Li, Guandong Xu

Graph Contrastive Learning (GCL) is a potent paradigm for self-supervised graph learning that has attracted attention across various application scenarios.

Contrastive Learning Data Augmentation +3

SSD4Rec: A Structured State Space Duality Model for Efficient Sequential Recommendation

2 code implementations2 Sep 2024 Haohao Qu, Yifeng Zhang, Liangbo Ning, Wenqi Fan, Qing Li

Sequential recommendation methods are crucial in modern recommender systems for their remarkable capability to understand a user's changing interests based on past interactions.

Mamba Sequential Recommendation +1

CoRe: Context-Regularized Text Embedding Learning for Text-to-Image Personalization

no code implementations28 Aug 2024 Feize Wu, Yun Pang, Junyi Zhang, Lianyu Pang, Jian Yin, Baoquan Zhao, Qing Li, Xudong Mao

This is based on the insight that appropriate output vectors of the text encoder for the context tokens can only be achieved if the new concept's text embedding is correctly learned.

Image Generation

Self-supervised Topic Taxonomy Discovery in the Box Embedding Space

no code implementations27 Aug 2024 Yuyin Lu, Hegang Chen, Pengbo Mao, Yanghui Rao, Haoran Xie, Fu Lee Wang, Qing Li

Topic taxonomy discovery aims at uncovering topics of different abstraction levels and constructing hierarchical relations between them.

Decentralised Variational Inference Frameworks for Multi-object Tracking on Sensor Networks: Additional Notes

no code implementations24 Aug 2024 Qing Li, Runze Gan, Simon Godsill

This paper tackles the challenge of multi-sensor multi-object tracking by proposing various decentralised Variational Inference (VI) schemes that match the tracking performance of centralised sensor fusion with only local message exchanges among neighboring sensors.

Multi-Object Tracking Object +2

Reasoning Factual Knowledge in Structured Data with Large Language Models

1 code implementation22 Aug 2024 Sirui Huang, Yanggan Gu, Xuming Hu, Zhonghao Li, Qing Li, Guandong Xu

This benchmark allows us to investigate the capability of LLMs across five factual tasks derived from the unique characteristics of structural facts.

Navigate

DATTA: Towards Diversity Adaptive Test-Time Adaptation in Dynamic Wild World

no code implementations15 Aug 2024 Chuyang Ye, Dongyan Wei, Zhendong Liu, Yuanyi Pang, Yixi Lin, Jiarong Liao, Qinting Jiang, Xianghua Fu, Qing Li, Jingyan Jiang

It features three key components: Diversity Discrimination (DD) to assess batch diversity, Diversity Adaptive Batch Normalization (DABN) to tailor normalization methods based on DD insights, and Diversity Adaptive Fine-Tuning (DAFT) to selectively fine-tune the model.

Diversity Test-time Adaptation

Reference-free Hallucination Detection for Large Vision-Language Models

no code implementations11 Aug 2024 Qing Li, Jiahui Geng, Chenyang Lyu, Derui Zhu, Maxim Panov, Fakhri Karray

In particular, we conduct an extensive study on three kinds of techniques: uncertainty-based, consistency-based, and supervised uncertainty quantification methods on four representative LVLMs across two different tasks.

Hallucination Question Answering +1

Task-oriented Sequential Grounding in 3D Scenes

no code implementations7 Aug 2024 Zhuofan Zhang, Ziyu Zhu, Pengxiang Li, Tengyu Liu, Xiaojian Ma, Yixin Chen, Baoxiong Jia, Siyuan Huang, Qing Li

Grounding natural language in physical 3D environments is essential for the advancement of embodied artificial intelligence.

3D visual grounding

Multi-weather Cross-view Geo-localization Using Denoising Diffusion Models

no code implementations5 Aug 2024 Tongtong Feng, Qing Li, Xin Wang, Mingzi Wang, Guangyao Li, Wenwu Zhu

For image restoration, MCGF incorporates a shared encoder and a lightweight restoration module to help the backbone eliminate weather-specific information.

Denoising geo-localization +1

Joint Universal Adversarial Perturbations with Interpretations

no code implementations3 Aug 2024 Liang-bo Ning, Zeyu Dai, Wenqi Fan, Jingran Su, Chao Pan, Luning Wang, Qing Li

Recent studies have shown that adversaries can manipulate the predictions of DNNs by adding a universal adversarial perturbation (UAP) to benign samples.

A Survey of Mamba

no code implementations2 Aug 2024 Haohao Qu, Liangbo Ning, Rui An, Wenqi Fan, Tyler Derr, Hui Liu, Xin Xu, Qing Li

In this survey, we therefore conduct an in-depth investigation of recent Mamba-associated studies, covering three main aspects: the advancements of Mamba-based models, the techniques of adapting Mamba to diverse data, and the applications where Mamba can excel.

Mamba State Space Models +1

LoopSparseGS: Loop Based Sparse-View Friendly Gaussian Splatting

no code implementations1 Aug 2024 Zhenyu Bao, Guibiao Liao, Kaichen Zhou, Kanglin Liu, Qing Li, Guoping Qiu

To handle these issues, we propose the LoopSparseGS, a loop-based 3DGS framework for the sparse novel view synthesis task.

3DGS Novel View Synthesis

Dynamic Universal Approximation Theory: Foundations for Parallelism in Neural Networks

no code implementations31 Jul 2024 Wei Wang, Qing Li

Neural networks are increasingly evolving towards training large models with big data, a method that has demonstrated superior performance across many tasks.

Deep Learning

Multi-Level Querying using A Knowledge Pyramid

no code implementations31 Jul 2024 Rubing Chen, Xulu Zhang, Jiaxin Wu, Wenqi Fan, Xiao-Yong Wei, Qing Li

We propose a multi-layer knowledge pyramid approach within the RAG framework to achieve a better balance between precision and recall.

Knowledge Graphs RAG +2

Prior Knowledge Integration via LLM Encoding and Pseudo Event Regulation for Video Moment Retrieval

1 code implementation21 Jul 2024 Yiyang Jiang, WengYu Zhang, Xulu Zhang, XiaoYong Wei, Chang Wen Chen, Qing Li

Through a feasibility study, we demonstrate that LLM encoders effectively refine inter-concept relations in multimodal embeddings, even without being trained on textual embeddings.

General Knowledge Highlight Detection +4

FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Models

no code implementations16 Jul 2024 Pengxiang Li, Zhi Gao, Bofei Zhang, Tao Yuan, Yuwei Wu, Mehrtash Harandi, Yunde Jia, Song-Chun Zhu, Qing Li

Vision language models (VLMs) have achieved impressive progress in diverse applications, becoming a prevalent research direction.

UltraEdit: Instruction-based Fine-Grained Image Editing at Scale

1 code implementation7 Jul 2024 Haozhe Zhao, Xiaojian Ma, Liang Chen, Shuzheng Si, Rujie Wu, Kaikai An, Peiyu Yu, Minjia Zhang, Qing Li, Baobao Chang

This paper presents UltraEdit, a large-scale (approximately 4 million editing samples), automatically generated dataset for instruction-based image editing.

Diversity +1

Backdoor Graph Condensation

1 code implementation3 Jul 2024 Jiahao Wu, Ning Lu, Zeiyu Dai, Kun Wang, Wenqi Fan, Shengcai Liu, Qing Li, Ke Tang

However, while existing graph condensation studies mainly focus on the best trade-off between graph size and the GNNs' performance (model utility), they overlook the security issues of graph condensation.

Backdoor Attack

RVISA: Reasoning and Verification for Implicit Sentiment Analysis

no code implementations2 Jul 2024 Wenna Lai, Haoran Xie, Guandong Xu, Qing Li

To identify implicit sentiment with reliable reasoning, this study proposes RVISA, a two-stage reasoning framework that harnesses the generation ability of DO LLMs and the reasoning ability of ED LLMs to train an enhanced reasoner.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +4

Dynamic Universal Approximation Theory: The Basic Theory for Deep Learning-Based Computer Vision Models

no code implementations2 Jul 2024 Wei Wang, Qing Li

What is the fundamental difference between residual-based CNNs and Transformer-based networks?

Dynamic Universal Approximation Theory: The Basic Theory for Transformer-based Large Language Models

no code implementations1 Jul 2024 Wei Wang, Qing Li

Language models have emerged as a critical area of focus in artificial intelligence, particularly with the introduction of groundbreaking innovations like ChatGPT.

In-Context Learning

OmniJARVIS: Unified Vision-Language-Action Tokenization Enables Open-World Instruction Following Agents

no code implementations27 Jun 2024 ZiHao Wang, Shaofei Cai, Zhancun Mu, Haowei Lin, Ceyao Zhang, Xuejie Liu, Qing Li, Anji Liu, Xiaojian Ma, Yitao Liang

First, we introduce a self-supervised approach to learn a behavior encoder that produces discretized tokens for behavior trajectories $\tau = \{o_0, a_0, \dots\}$ and an imitation learning policy decoder conditioned on these tokens.

Decoder Imitation Learning +4

Make Your Home Safe: Time-aware Unsupervised User Behavior Anomaly Detection in Smart Homes via Loss-guided Mask

1 code implementation16 Jun 2024 Jingyu Xiao, Zhiyao Xu, Qingsong Zou, Qing Li, Dan Zhao, Dong Fang, Ruoyu Li, Wenxin Tang, Kang Li, Xudong Zuo, Penghui Hu, Yong Jiang, Zixuan Weng, Michael R. Lyv

However, their performance often falls short because they do not effectively learn less frequent behaviors, consider temporal context, or account for the impact of noise in human behaviors.

Anomaly Detection

TokenRec: Learning to Tokenize ID for LLM-based Generative Recommendation

no code implementations15 Jun 2024 Haohao Qu, Wenqi Fan, Zihuai Zhao, Qing Li

There is a growing interest in utilizing large-scale language models (LLMs) to advance next-generation Recommender Systems (RecSys), driven by their outstanding language understanding and in-context learning capabilities.

Collaborative Filtering In-Context Learning +2

FIRM: Flexible Interactive Reflection reMoval

1 code implementation3 Jun 2024 Xiao Chen, Xudong Jiang, Yunkang Tao, Zhen Lei, Qing Li, Chenyang Lei, Zhaoxiang Zhang

Secondly, we devise a contrastive mask-guided reflection removal network that comprises a newly proposed contrastive guidance interaction block (CGIB).

Interactive Segmentation Reflection Removal

MGCP: A Multi-Grained Correlation based Prediction Network for Multivariate Time Series

no code implementations30 May 2024 Zhicheng Chen, Xi Xiao, Ke Xu, Zhong Zhang, Yu Rong, Qing Li, Guojun Gan, Zhiqiang Xu, Peilin Zhao

Multivariate time series prediction is widely used in daily life, which poses significant challenges due to the complex correlations that exist at multi-grained levels.

Prediction Time Series +1

Expert-Guided Extinction of Toxic Tokens for Debiased Generation

no code implementations29 May 2024 Xueyao Sun, Kaize Shi, Haoran Tang, Guandong Xu, Qing Li

Large language models (LLMs) can elicit social bias during generations, especially when inference with toxic prompts.

Fairness Retrieval

Unifying 3D Vision-Language Understanding via Promptable Queries

no code implementations19 May 2024 Ziyu Zhu, Zhuofan Zhang, Xiaojian Ma, Xuesong Niu, Yixin Chen, Baoxiong Jia, Zhidong Deng, Siyuan Huang, Qing Li

A unified model for 3D vision-language (3D-VL) understanding is expected to take various scene representations and perform a wide range of tasks in a 3D scene.

3D Question Answering (3D-QA) Decoder +3

A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models

no code implementations10 May 2024 Wenqi Fan, Yujuan Ding, Liangbo Ning, Shijie Wang, Hengyun Li, Dawei Yin, Tat-Seng Chua, Qing Li

Given the powerful abilities of RAG in providing the latest and helpful auxiliary information, Retrieval-Augmented Large Language Models (RA-LLMs) have emerged to harness external and authoritative knowledge bases, rather than solely relying on the model's internal knowledge, to augment the generation quality of LLMs.

Information Retrieval RAG +2

Compressing Long Context for Enhancing RAG with AMR-based Concept Distillation

no code implementations6 May 2024 Kaize Shi, Xueyao Sun, Qing Li, Guandong Xu

The proposed algorithm compresses the cluttered raw retrieved documents into a compact set of crucial concepts distilled from the informative nodes of AMR by referring to reliable linguistic features.

Abstract Meaning Representation Open-Domain Question Answering +3

SlotGAT: Slot-based Message Passing for Heterogeneous Graph Neural Network

1 code implementation3 May 2024 Ziang Zhou, Jieming Shi, Renchi Yang, Yuanhang Zou, Qing Li

We identify a potential semantic mixing issue in existing message passing processes, where the representations of the neighbors of a node $v$ are forced to be transformed to the feature space of $v$ for aggregation, though the neighbors are in different types.

Graph Neural Network Heterogeneous Node Classification +1

Graph Machine Learning in the Era of Large Language Models (LLMs)

no code implementations23 Apr 2024 Wenqi Fan, Shijie Wang, Jiani Huang, Zhikai Chen, Yu Song, Wenzhuo Tang, Haitao Mao, Hui Liu, Xiaorui Liu, Dawei Yin, Qing Li

Meanwhile, graphs, especially knowledge graphs, are rich in reliable factual knowledge, which can be utilized to enhance the reasoning capabilities of LLMs and potentially alleviate their limitations such as hallucinations and the lack of explainability.

Few-Shot Learning Knowledge Graphs +1

CLIP-GS: CLIP-Informed Gaussian Splatting for Real-time and View-consistent 3D Semantic Understanding

1 code implementation22 Apr 2024 Guibiao Liao, Jiankun Li, Zhenyu Bao, Xiaoqing Ye, Jingdong Wang, Qing Li, Kanglin Liu

Additionally, to address the semantic ambiguity, caused by utilizing view-inconsistent 2D CLIP semantics to supervise Gaussians, we introduce a 3D Coherent Self-training (3DCS) strategy, resorting to the multi-view consistency originated from the 3D model.

Attribute

MaterialSeg3D: Segmenting Dense Materials from 2D Priors for 3D Assets

no code implementations22 Apr 2024 Zeyu Li, Ruitong Gan, Chuanchen Luo, Yuxi Wang, Jiaheng Liu, Ziwei Zhu Man Zhang, Qing Li, XuCheng Yin, Zhaoxiang Zhang, Junran Peng

Driven by powerful image diffusion models, recent research has achieved the automatic creation of 3D objects from textual or visual guidance.

Advancing the Robustness of Large Language Models through Self-Denoised Smoothing

1 code implementation18 Apr 2024 Jiabao Ji, Bairu Hou, Zhen Zhang, Guanhua Zhang, Wenqi Fan, Qing Li, Yang Zhang, Gaowen Liu, Sijia Liu, Shiyu Chang

Although large language models (LLMs) have achieved significant success, their vulnerability to adversarial perturbations, including recent jailbreak attacks, has raised considerable concerns.

PoLLMgraph: Unraveling Hallucinations in Large Language Models via State Transition Dynamics

1 code implementation6 Apr 2024 Derui Zhu, Dingfan Chen, Qing Li, Zongxiong Chen, Lei Ma, Jens Grossklags, Mario Fritz

Despite tremendous advancements in large language models (LLMs) over recent years, a notably urgent challenge for their practical deployment is the phenomenon of hallucination, where the model fabricates facts and produces non-factual statements.

Benchmarking Hallucination +1

A Picture Is Worth a Graph: A Blueprint Debate Paradigm for Multimodal Reasoning

1 code implementation22 Mar 2024 Changmeng Zheng, Dayong Liang, WengYu Zhang, Xiao-Yong Wei, Tat-Seng Chua, Qing Li

The study addresses two key challenges: the trivialization of opinions resulting from excessive summarization and the diversion of focus caused by distractor concepts introduced from images.

Multimodal Reasoning

Generative Active Learning for Image Synthesis Personalization

1 code implementation22 Mar 2024 Xulu Zhang, WengYu Zhang, Xiao-Yong Wei, Jinlin Wu, Zhaoxiang Zhang, Zhen Lei, Qing Li

The primary challenge in conducting active learning on generative models lies in the open-ended nature of querying, which differs from the closed form of querying in discriminative models that typically target a single concept.

Active Learning Image Generation

Semantic Gaussians: Open-Vocabulary Scene Understanding with 3D Gaussian Splatting

no code implementations22 Mar 2024 Jun Guo, Xiaojian Ma, Yue Fan, Huaping Liu, Qing Li

Unlike existing methods, we design a versatile projection approach that maps various 2D semantic features from pre-trained image encoders into a novel semantic component of 3D Gaussians, which is based on spatial relationship and need no additional training.

Instance Segmentation Object Localization +4

End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations

1 code implementation19 Mar 2024 Lirui Luo, Guoxi Zhang, Hongming Xu, Yaodong Yang, Cong Fang, Qing Li

Neuro-symbolic reinforcement learning (NS-RL) has emerged as a promising paradigm for explainable decision-making, characterized by the interpretability of symbolic policies.

Decision Making reinforcement-learning +1

VideoAgent: A Memory-augmented Multimodal Agent for Video Understanding

no code implementations18 Mar 2024 Yue Fan, Xiaojian Ma, Rujie Wu, Yuntao Du, Jiaqi Li, Zhi Gao, Qing Li

We explore how reconciling several foundation models (large language models and vision-language models) with a novel unified memory mechanism could tackle the challenging video understanding problem, especially capturing the long-term temporal relations in lengthy videos.

EgoSchema Video Understanding

FashionReGen: LLM-Empowered Fashion Report Generation

1 code implementation11 Mar 2024 Yujuan Ding, Yunshan Ma, Wenqi Fan, Yige Yao, Tat-Seng Chua, Qing Li

Fashion analysis refers to the process of examining and evaluating trends, styles, and elements within the fashion industry to understand and interpret its current state, generating fashion reports.

Large Language Models are In-Context Molecule Learners

1 code implementation7 Mar 2024 Jiatong Li, Wei Liu, Zhihao Ding, Wenqi Fan, Yuqiang Li, Qing Li

Large Language Models (LLMs) have demonstrated exceptional performance in biochemical tasks, especially the molecule caption translation task, which aims to bridge the gap between molecules and natural language texts.

Cross-Modal Retrieval In-Context Learning +3

2D Matryoshka Sentence Embeddings

1 code implementation22 Feb 2024 Xianming Li, Zongxi Li, Jing Li, Haoran Xie, Qing Li

The experimental results demonstrate the effectiveness of our proposed model in dynamically supporting different embedding sizes and Transformer layers, allowing it to be highly adaptable to various scenarios.

RAG Retrieval +5

Linear-Time Graph Neural Networks for Scalable Recommendations

1 code implementation21 Feb 2024 Jiahao Zhang, Rui Xue, Wenqi Fan, Xin Xu, Qing Li, Jian Pei, Xiaorui Liu

In this paper, we propose a Linear-Time Graph Neural Network (LTGNN) to scale up GNN-based recommender systems to achieve comparable scalability as classic MF approaches while maintaining GNNs' powerful expressiveness for superior prediction accuracy.

Graph Neural Network

One Train for Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive Learning

1 code implementation12 Feb 2024 Haozhen Zhang, Xi Xiao, Le Yu, Qing Li, Zhen Ling, Ye Zhang

In particular, we utilize supervised contrastive learning to enhance the packet-level and flow-level representations and perform graph data augmentation on the byte-level traffic graph so that the fine-grained semantic-invariant characteristics between bytes can be captured through contrastive learning.

Classification Contrastive Learning +3

OV-NeRF: Open-vocabulary Neural Radiance Fields with Vision and Language Foundation Models for 3D Semantic Understanding

1 code implementation7 Feb 2024 Guibiao Liao, Kaichen Zhou, Zhenyu Bao, Kanglin Liu, Qing Li

Second, from the cross-view perspective, we propose a Cross-view Self-enhancement (CSE) strategy to address the challenge raised by view-inconsistent semantics.

NeRF

Progress and Opportunities of Foundation Models in Bioinformatics

no code implementations6 Feb 2024 Qing Li, Zhihang Hu, YiXuan Wang, Lei LI, Yimin Fan, Irwin King, Le Song, Yu Li

Central to our focus is the application of FMs to specific biological problems, aiming to guide the research community in choosing appropriate FMs for their research needs.

Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey

1 code implementation3 Feb 2024 Yi Xin, Jianjiang Yang, Siqi Luo, Haodi Zhou, Junlong Du, Xiaohong Liu, Yue Fan, Qing Li, Yuntao Du

Large-scale pre-trained vision models (PVMs) have shown great potential for adaptability across various downstream vision tasks.

parameter-efficient fine-tuning Transfer Learning

SAGD: Boundary-Enhanced Segment Anything in 3D Gaussian via Gaussian Decomposition

1 code implementation31 Jan 2024 Xu Hu, Yuxi Wang, Lue Fan, Chuanchen Luo, Junsong Fan, Zhen Lei, Qing Li, Junran Peng, Zhaoxiang Zhang

3D Gaussian Splatting has emerged as an alternative 3D representation for novel view synthesis, benefiting from its high-quality rendering results and real-time rendering speed.

Novel View Synthesis Segmentation +1

One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training

1 code implementation30 Jan 2024 Lianbo Ma, Yuee Zhou, Jianlun Ma, Guo Yu, Qing Li

During the gradient descent learning, a one-step forward search is designed to find the trial gradient of the next-step, which is adopted to adjust the gradient of current step towards the direction of fast convergence.

Quantization

3D Reconstruction and New View Synthesis of Indoor Environments based on a Dual Neural Radiance Field

1 code implementation26 Jan 2024 Zhenyu Bao, Guibiao Liao, Zhongyuan Zhao, Kanglin Liu, Qing Li, Guoping Qiu

One of the innovative features of Du-NeRF is that it decouples a view-independent component from the density field and uses it as a label to supervise the learning process of the SDF field.

3D Reconstruction NeRF +1

PSAvatar: A Point-based Shape Model for Real-Time Head Avatar Animation with 3D Gaussian Splatting

1 code implementation23 Jan 2024 Zhongyuan Zhao, Zhenyu Bao, Qing Li, Guoping Qiu, Kanglin Liu

In this paper, we introduce PSAvatar, a novel framework for animatable head avatar creation that utilizes discrete geometric primitive to create a parametric morphable shape model and employs 3D Gaussian for fine detail representation and high fidelity rendering.

SceneVerse: Scaling 3D Vision-Language Learning for Grounded Scene Understanding

no code implementations17 Jan 2024 Baoxiong Jia, Yixin Chen, Huangyue Yu, Yan Wang, Xuesong Niu, Tengyu Liu, Qing Li, Siyuan Huang

In comparison to recent advancements in the 2D domain, grounding language in 3D scenes faces several significant challenges: (i) the inherent complexity of 3D scenes due to the diverse object configurations, their rich attributes, and intricate relationships; (ii) the scarcity of paired 3D vision-language data to support grounded learning; and (iii) the absence of a unified learning framework to distill knowledge from grounded 3D data.

3D visual grounding Scene Understanding

Developing ChatGPT for Biology and Medicine: A Complete Review of Biomedical Question Answering

no code implementations15 Jan 2024 Qing Li, Lei LI, Yu Li

Central to our focus is the utilizing of language models and multimodal paradigms for medical question answering, aiming to guide the research community in selecting appropriate mechanisms for their specific medical research requirements.

Cross-Modal Retrieval Medical Diagnosis +4

3D Landmark Detection on Human Point Clouds: A Benchmark and A Dual Cascade Point Transformer Framework

no code implementations14 Jan 2024 Fan Zhang, Shuyi Mao, Qing Li, Xiaojiang Peng

Comparative evaluations with popular point-based methods on HPoint103 and the public dataset DHP19 demonstrate the dramatic outperformance of our D-CPT.

Decoder Pose Estimation +1

Quantized Side Tuning: Fast and Memory-Efficient Tuning of Quantized Large Language Models

1 code implementation13 Jan 2024 Zhengxin Zhang, Dan Zhao, Xupeng Miao, Gabriele Oliaro, Qing Li, Yong Jiang, Zhihao Jia

Experiments show that QST can reduce the total memory footprint by up to 2. 3 $\times$ and speed up the finetuning process by up to 3 $\times$ while achieving competent performance compared with the state-of-the-art.

Cross Initialization for Face Personalization of Text-to-Image Models

1 code implementation CVPR 2024 Lianyu Pang, Jian Yin, Haoran Xie, Qiping Wang, Qing Li, Xudong Mao

Additionally a fast version of our method allows for capturing an input image in roughly 26 seconds while surpassing the baseline methods in terms of both reconstruction and editability.

Cross Initialization for Personalized Text-to-Image Generation

1 code implementation26 Dec 2023 Lianyu Pang, Jian Yin, Haoran Xie, Qiping Wang, Qing Li, Xudong Mao

Additionally, a fast version of our method allows for capturing an input image in roughly 26 seconds, while surpassing the baseline methods in terms of both reconstruction and editability.

Text to Image Generation Text-to-Image Generation

CLOVA: A Closed-Loop Visual Assistant with Tool Usage and Update

no code implementations CVPR 2024 Zhi Gao, Yuntao Du, Xintong Zhang, Xiaojian Ma, Wenjuan Han, Song-Chun Zhu, Qing Li

However, these methods often overlook the potential for continual learning, typically by freezing the utilized tools, thus limiting their adaptation to environments requiring new knowledge.

Continual Learning Question Answering +1

Compositional Inversion for Stable Diffusion Models

1 code implementation13 Dec 2023 Xulu Zhang, Xiao-Yong Wei, Jinlin Wu, Tianyi Zhang, Zhaoxiang Zhang, Zhen Lei, Qing Li

It stems from the fact that during inversion, the irrelevant semantics in the user images are also encoded, forcing the inverted concepts to occupy locations far from the core distribution in the embedding space.

Recognizing Conditional Causal Relationships about Emotions and Their Corresponding Conditions

no code implementations28 Nov 2023 Xinhong Chen, Zongxi Li, YaoWei Wang, Haoran Xie, JianPing Wang, Qing Li

To highlight the context in such special causal relationships, we propose a new task to determine whether or not an input pair of emotion and cause has a valid causal relationship under different contexts and extract the specific context clauses that participate in the causal relationship.

valid

An Embodied Generalist Agent in 3D World

1 code implementation18 Nov 2023 Jiangyong Huang, Silong Yong, Xiaojian Ma, Xiongkun Linghu, Puhao Li, Yan Wang, Qing Li, Song-Chun Zhu, Baoxiong Jia, Siyuan Huang

However, several significant challenges remain: (i) most of these models rely on 2D images yet exhibit a limited capacity for 3D input; (ii) these models rarely explore the tasks inherently defined in 3D world, e. g., 3D grounding, embodied reasoning and acting.

3D dense captioning 3D Question Answering (3D-QA) +4

Multi-agent Attacks for Black-box Social Recommendations

no code implementations13 Nov 2023 Shijie Wang, Wenqi Fan, Xiao-Yong Wei, Xiaowei Mei, Shanru Lin, Qing Li

To perform untargeted attacks on social recommender systems, attackers can construct malicious social relationships for fake users to enhance the attack performance.

Decision Making Multi-agent Reinforcement Learning +1

NeuralGF: Unsupervised Point Normal Estimation by Learning Neural Gradient Function

1 code implementation NeurIPS 2023 Qing Li, Huifang Feng, Kanle Shi, Yue Gao, Yi Fang, Yu-Shen Liu, Zhizhong Han

Specifically, we introduce loss functions to facilitate query points to iteratively reach the moving targets and aggregate onto the approximated surface, thereby learning a global surface representation of the data.

3D geometry

Embedding in Recommender Systems: A Survey

1 code implementation28 Oct 2023 Xiangyu Zhao, Maolin Wang, Xinjian Zhao, Jiansheng Li, Shucheng Zhou, Dawei Yin, Qing Li, Jiliang Tang, Ruocheng Guo

This survey covers embedding methods like collaborative filtering, self-supervised learning, and graph-based techniques.

AutoML Collaborative Filtering +4

Fast Graph Condensation with Structure-based Neural Tangent Kernel

1 code implementation17 Oct 2023 Lin Wang, Wenqi Fan, Jiatong Li, Yao Ma, Qing Li

The rapid development of Internet technology has given rise to a vast amount of graph-structured data.

Dataset Condensation Graph Mining

Bongard-OpenWorld: Few-Shot Reasoning for Free-form Visual Concepts in the Real World

1 code implementation16 Oct 2023 Rujie Wu, Xiaojian Ma, Zhenliang Zhang, Wei Wang, Qing Li, Song-Chun Zhu, Yizhou Wang

We even conceived a neuro-symbolic reasoning approach that reconciles LLMs & VLMs with logical reasoning to emulate the human problem-solving process for Bongard Problems.

Few-Shot Learning Form +2

Multi-Scale Spatial-Temporal Recurrent Networks for Traffic Flow Prediction

no code implementations12 Oct 2023 Haiyang Liu, Chunjiang Zhu, Detian Zhang, Qing Li

Traffic flow prediction is one of the most fundamental tasks of intelligent transportation systems.

Prediction

Label Supervised LLaMA Finetuning

2 code implementations2 Oct 2023 Zongxi Li, Xianming Li, Yuzhang Liu, Haoran Xie, Jing Li, Fu-lee Wang, Qing Li, Xiaoqin Zhong

We evaluate this approach with Label Supervised LLaMA (LS-LLaMA), based on LLaMA-2-7B, a relatively small-scale LLM, and can be finetuned on a single GeForce RTX4090 GPU.

 Ranked #1 on Named Entity Recognition (NER) on CoNLL03 (F1 (micro) metric)

named-entity-recognition Named Entity Recognition +7

Dataset Condensation for Recommendation

1 code implementation2 Oct 2023 Jiahao Wu, Wenqi Fan, Jingfan Chen, Shengcai Liu, Qijiong Liu, Rui He, Qing Li, Ke Tang

Specifically, we model the discrete user-item interactions via a probabilistic approach and design a pre-augmentation module to incorporate the potential preferences of users into the condensed datasets.

Dataset Condensation

Enhancing Graph Collaborative Filtering via Uniformly Co-Clustered Intent Modeling

no code implementations22 Sep 2023 Jiahao Wu, Wenqi Fan, Shengcai Liu, Qijiong Liu, Qing Li, Ke Tang

To model the compatibility between user intents and item properties, we design the user-item co-clustering module, maximizing the mutual information of co-clusters of users and items.

Collaborative Filtering

Neural Gradient Learning and Optimization for Oriented Point Normal Estimation

1 code implementation17 Sep 2023 Qing Li, Huifang Feng, Kanle Shi, Yi Fang, Yu-Shen Liu, Zhizhong Han

We propose Neural Gradient Learning (NGL), a deep learning approach to learn gradient vectors with consistent orientation from 3D point clouds for normal estimation.

Effective Illicit Account Detection on Large Cryptocurrency MultiGraphs

1 code implementation4 Sep 2023 Zhihao Ding, Jieming Shi, Qing Li, Jiannong Cao

For example, on a Bitcoin dataset with 20 million nodes and 203 million edges, DIAM attains an F1 score of 96. 55%, markedly surpassing the runner-up's score of 83. 92%.

Feature Engineering Graph Neural Network

Variational Tracking and Redetection for Closely-spaced Objects in Heavy Clutter: Supplementary Materials

no code implementations4 Sep 2023 Runze Gan, Qing Li, Simon Godsill

The non-homogeneous Poisson process (NHPP) is a widely used measurement model that allows for an object to generate multiple measurements over time.

Consensus-based Distributed Variational Multi-object Tracker in Multi-Sensor Network

no code implementations2 Sep 2023 Qing Li, Runze Gan, Simon Godsill

Then, we develop a distributed version leveraging the average consensus algorithm, which is theoretically equivalent to the centralised sensor fusion tracker and requires only local message passing with neighbouring sensors.

Object Tracking Sensor Fusion

LLaMA-E: Empowering E-commerce Authoring with Object-Interleaved Instruction Following

no code implementations9 Aug 2023 Kaize Shi, Xueyao Sun, Dingxian Wang, Yinlin Fu, Guandong Xu, Qing Li

E-commerce authoring entails creating engaging, diverse, and targeted content to enhance preference elicitation and retrieval experience.

Common Sense Reasoning Instruction Following +1

3D-VisTA: Pre-trained Transformer for 3D Vision and Text Alignment

1 code implementation ICCV 2023 Ziyu Zhu, Xiaojian Ma, Yixin Chen, Zhidong Deng, Siyuan Huang, Qing Li

3D vision-language grounding (3D-VL) is an emerging field that aims to connect the 3D physical world with natural language, which is crucial for achieving embodied intelligence.

3D Question Answering (3D-QA) Dense Captioning +4

DiffusePast: Diffusion-based Generative Replay for Class Incremental Semantic Segmentation

no code implementations2 Aug 2023 Jingfan Chen, Yuxi Wang, Pengfei Wang, Xiao Chen, Zhaoxiang Zhang, Zhen Lei, Qing Li

The Class Incremental Semantic Segmentation (CISS) extends the traditional segmentation task by incrementally learning newly added classes.

Class-Incremental Semantic Segmentation Segmentation

Certified Robustness for Large Language Models with Self-Denoising

1 code implementation14 Jul 2023 Zhen Zhang, Guanhua Zhang, Bairu Hou, Wenqi Fan, Qing Li, Sijia Liu, Yang Zhang, Shiyu Chang

This largely falls into the study of certified robust LLMs, i. e., all predictions of LLM are certified to be correct in a local region around the input.

Denoising

Counterfactual Explanation for Fairness in Recommendation

no code implementations10 Jul 2023 Xiangmeng Wang, Qian Li, Dianer Yu, Qing Li, Guandong Xu

The counterfactual explanations help to provide rational and proximate explanations for model fairness, while the attentive action pruning narrows the search space of attributes.

Attribute Causal Inference +4

STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction

2 code implementations2 Jul 2023 Xunlian Luo, Chunjiang Zhu, Detian Zhang, Qing Li

However, a survey study of graph learning, spatial-temporal graph models for traffic, as well as a fair comparison of baseline models are pending and unavoidable issues.

Graph Learning Traffic Prediction

Farthest Streamline Sampling for the Uniform Distribution of Forearm Muscle Fiber Tracts from Diffusion Tensor Imaging

no code implementations24 Jun 2023 Yang Li, Shihan Ma, Jiamin Zhao, Qing Li, Xinjun Sheng

FSS reduced the sampling of long tracts (10% reduction in fiber length, P<0. 05), and the architectural parameters were within physiological ranges (two parameters with P<0. 05).

Recurrent Attention Networks for Long-text Modeling

1 code implementation12 Jun 2023 Xianming Li, Zongxi Li, Xiaotian Luo, Haoran Xie, Xing Lee, Yingbin Zhao, Fu Lee Wang, Qing Li

Revisiting the self-attention mechanism and the recurrent structure, this paper proposes a novel long-document encoding model, Recurrent Attention Network (RAN), to enable the recurrent operation of self-attention.

Chunking

Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective

1 code implementation11 Jun 2023 Jiatong Li, Yunqing Liu, Wenqi Fan, Xiao-Yong Wei, Hui Liu, Jiliang Tang, Qing Li

In this work, we propose a novel LLM-based framework (MolReGPT) for molecule-caption translation, where an In-Context Few-Shot Molecule Learning paradigm is introduced to empower molecule discovery with LLMs like ChatGPT to perform their in-context learning capability without domain-specific pre-training and fine-tuning.

In-Context Learning Molecule Captioning +3

FERN: Leveraging Graph Attention Networks for Failure Evaluation and Robust Network Design

no code implementations30 May 2023 Chenyi Liu, Vaneet Aggarwal, Tian Lan, Nan Geng, Yuan Yang, Mingwei Xu, Qing Li

By providing a neural network function approximation of this common kernel using graph attention networks, we develop a unified learning-based framework, FERN, for scalable Failure Evaluation and Robust Network design.

Graph Attention

Inferring Attracting Basins of Power System with Machine Learning

no code implementations20 May 2023 Yao Du, Qing Li, Huawei Fan, Meng Zhan, Jinghua Xiao, Xingang Wang

Power systems dominated by renewable energy encounter frequently large, random disturbances, and a critical challenge faced in power-system management is how to anticipate accurately whether the perturbed systems will return to the functional state after the transient or collapse.

Learning Signed Hyper Surfaces for Oriented Point Cloud Normal Estimation

1 code implementation CVPR 2023 Qing Li, Huifang Feng, Kanle Shi, Yue Gao, Yi Fang, Yu-Shen Liu, Zhizhong Han

In this work, we introduce signed hyper surfaces (SHS), which are parameterized by multi-layer perceptron (MLP) layers, to learn to estimate oriented normals from point clouds in an end-to-end manner.

Decoder

Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy

no code implementations10 May 2023 Thanveer Shaik, Xiaohui Tao, Haoran Xie, Lin Li, Xiaofeng Zhu, Qing Li

Machine unlearning (MU) is gaining increasing attention due to the need to remove or modify predictions made by machine learning (ML) models.

Fairness Machine Unlearning +1

Unlocking the Power of GANs in Non-Autoregressive Text Generation

no code implementations6 May 2023 Da Ren, Yi Cai, Qing Li

Generative Adversarial Networks (GANs) have been studied in text generation to tackle the exposure bias problem.

Position Text Generation

MD-Manifold: A Medical-Distance-Based Representation Learning Approach for Medical Concept and Patient Representation

no code implementations30 Apr 2023 Shaodong Wang, Qing Li, Wenli Zhang

Representing medical concepts for healthcare analytical tasks requires incorporating medical domain knowledge and prior information from patient description data.

Data Augmentation Feature Engineering +1

Attention-based Spatial-Temporal Graph Convolutional Recurrent Networks for Traffic Forecasting

no code implementations25 Feb 2023 Haiyang Liu, Chunjiang Zhu, Detian Zhang, Qing Li

The key challenge is to effectively model complex spatial-temporal dependencies and correlations in modern traffic data.

Dynamic Graph Convolutional Network with Attention Fusion for Traffic Flow Prediction

1 code implementation24 Feb 2023 Xunlian Luo, Chunjiang Zhu, Detian Zhang, Qing Li

Accurate and real-time traffic state prediction is of great practical importance for urban traffic control and web mapping services.

Fairly Adaptive Negative Sampling for Recommendations

no code implementations16 Feb 2023 Xiao Chen, Wenqi Fan, Jingfan Chen, Haochen Liu, Zitao Liu, Zhaoxiang Zhang, Qing Li

Pairwise learning strategies are prevalent for optimizing recommendation models on implicit feedback data, which usually learns user preference by discriminating between positive (i. e., clicked by a user) and negative items (i. e., obtained by negative sampling).

Attribute Fairness

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