Search Results for author: Hao Wang

Found 493 papers, 154 papers with code

融合零指代识别的篇章级机器翻译(Context-aware Machine Translation Integrating Zero Pronoun Recognition)

no code implementations CCL 2021 Hao Wang, Junhui Li, ZhengXian Gong

“在汉语等其他有省略代词习惯的语言中, 通常会删掉可从上下文信息推断出的代词。尽管以Transformer为代表的的神经机器翻译模型取得了巨大的成功, 但这种省略现象依旧对神经机器翻译模型造成了很大的挑战。本文在Transformer基础上提出了一个融合零指代识别的翻译模型, 并引入篇章上下文来丰富指代信息。具体地, 该模型采用联合学习的框架, 在翻译模型基础上, 联合了一个分类任务, 即判别句子中省略代词在句子所表示的成分, 使得模型能够融合零指代信息辅助翻译。通过在中英对话数据集上的实验, 验证了本文提出方法的有效性, 与基准模型相比, 翻译性能提升了1. 48个BLEU值。”

Machine Translation

Toward Knowledge-Enriched Conversational Recommendation Systems

no code implementations NLP4ConvAI (ACL) 2022 Tong Zhang, Yong liu, Boyang Li, Peixiang Zhong, Chen Zhang, Hao Wang, Chunyan Miao

Conversational Recommendation Systems recommend items through language based interactions with users. In order to generate naturalistic conversations and effectively utilize knowledge graphs (KGs) containing background information, we propose a novel Bag-of-Entities loss, which encourages the generated utterances to mention concepts related to the item being recommended, such as the genre or director of a movie.

Knowledge Graphs Recommendation Systems +1

Beyond 3DMM Space: Towards Fine-grained 3D Face Reconstruction

1 code implementation ECCV 2020 Xiangyu Zhu, Fan Yang, Di Huang, Chang Yu, Hao Wang, Jianzhu Guo, Zhen Lei, Stan Z. Li

However, most of their training data is constructed by 3D Morphable Model, whose space spanned is only a small part of the shape space.

3D Face Reconstruction

CGI-DM: Digital Copyright Authentication for Diffusion Models via Contrasting Gradient Inversion

no code implementations17 Mar 2024 Xiaoyu Wu, Yang Hua, Chumeng Liang, Jiaru Zhang, Hao Wang, Tao Song, Haibing Guan

In response, we present Contrasting Gradient Inversion for Diffusion Models (CGI-DM), a novel method featuring vivid visual representations for digital copyright authentication.

StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models

1 code implementation12 Mar 2024 Zhicheng Guo, Sijie Cheng, Hao Wang, Shihao Liang, Yujia Qin, Peng Li, Zhiyuan Liu, Maosong Sun, Yang Liu

The virtual API server contains a caching system and API simulators which are complementary to alleviate the change in API status.

Benchmarking

Enhancing Plausibility Evaluation for Generated Designs with Denoising Autoencoder

no code implementations8 Mar 2024 Jiajie Fan, Amal Trigui, Thomas Bäck, Hao Wang

As such, FID might not be suitable to assess the performance of DGMs for a generative design task.

Denoising

Beyond MOT: Semantic Multi-Object Tracking

no code implementations8 Mar 2024 Yunhao Li, Hao Wang, Xue Ma, Jiali Yao, Shaohua Dong, Heng Fan, Libo Zhang

Current multi-object tracking (MOT) aims to predict trajectories of targets (i. e.,"where") in videos.

Multi-Object Tracking Object +1

AO-DETR: Anti-Overlapping DETR for X-Ray Prohibited Items Detection

1 code implementation7 Mar 2024 Mingyuan Li, Tong Jia, Hao Wang, Bowen Ma, Shuyang Lin, Da Cai, Dongyue Chen

Considering the significant overlapping phenomenon in X-ray prohibited item images, we propose an Anti-Overlapping DETR (AO-DETR) based on one of the state-of-the-art general object detectors, DINO.

FLAME Diffuser: Grounded Wildfire Image Synthesis using Mask Guided Diffusion

no code implementations6 Mar 2024 Hao Wang, Sayed Pedram Haeri Boroujeni, Xiwen Chen, Ashish Bastola, Huayu Li, Abolfazl Razi

Thus, our proposed framework can generate a massive dataset of that images are high-quality and ground truth-paired, which well addresses the needs of the annotated datasets in specific tasks.

Fire Detection Image Generation +2

Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language Models

no code implementations6 Mar 2024 Wenfeng Feng, Chuzhan Hao, Yuewei Zhang, Yu Han, Hao Wang

These LoRA modules can be aligned with the expert design principles observed in Mixture-of-Experts (MoE).

Multi-Task Learning

DOZE: A Dataset for Open-Vocabulary Zero-Shot Object Navigation in Dynamic Environments

no code implementations29 Feb 2024 Ji Ma, Hongming Dai, Yao Mu, Pengying Wu, Hao Wang, Xiaowei Chi, Yang Fei, Shanghang Zhang, Chang Liu

Zero-Shot Object Navigation (ZSON) requires agents to autonomously locate and approach unseen objects in unfamiliar environments and has emerged as a particularly challenging task within the domain of Embodied AI.

Attribute Collision Avoidance +2

Temporal-Aware Deep Reinforcement Learning for Energy Storage Bidding in Energy and Contingency Reserve Markets

no code implementations29 Feb 2024 Jinhao Li, Changlong Wang, Yanru Zhang, Hao Wang

To bridge this gap, we develop a novel BESS joint bidding strategy that utilizes deep reinforcement learning (DRL) to bid in the spot and contingency frequency control ancillary services (FCAS) markets.

All in a Single Image: Large Multimodal Models are In-Image Learners

1 code implementation28 Feb 2024 Lei Wang, Wanyu Xu, Zhiqiang Hu, Yihuai Lan, Shan Dong, Hao Wang, Roy Ka-Wei Lee, Ee-Peng Lim

This paper introduces a new in-context learning (ICL) mechanism called In-Image Learning (I$^2$L) that combines demonstration examples, visual cues, and instructions into a single image to enhance the capabilities of GPT-4V.

Hallucination In-Context Learning +1

CLAP: Learning Transferable Binary Code Representations with Natural Language Supervision

1 code implementation26 Feb 2024 Hao Wang, Zeyu Gao, Chao Zhang, Zihan Sha, Mingyang Sun, Yuchen Zhou, Wenyu Zhu, Wenju Sun, Han Qiu, Xi Xiao

At the core, our approach boosts superior transfer learning capabilities by effectively aligning binary code with their semantics explanations (in natural language), resulting a model able to generate better embeddings for binary code.

Representation Learning Transfer Learning

Gradient-Guided Modality Decoupling for Missing-Modality Robustness

no code implementations26 Feb 2024 Hao Wang, Shengda Luo, Guosheng Hu, JianGuo Zhang

In aid of this indicator, we present a novel Gradient-guided Modality Decoupling (GMD) method to decouple the dependency on dominating modalities.

Sentiment Analysis

From Noise to Clarity: Unraveling the Adversarial Suffix of Large Language Model Attacks via Translation of Text Embeddings

no code implementations25 Feb 2024 Hao Wang, Hao Li, Minlie Huang, Lei Sha

The safety defense methods of Large language models(LLMs) stays limited because the dangerous prompts are manually curated to just few known attack types, which fails to keep pace with emerging varieties.

Language Modelling Large Language Model

Building Flexible Machine Learning Models for Scientific Computing at Scale

no code implementations25 Feb 2024 Tianyu Chen, Haoyi Zhou, Ying Li, Hao Wang, Chonghan Gao, Shanghang Zhang, JianXin Li

Foundation models have revolutionized knowledge acquisition across domains, and our study introduces OmniArch, a paradigm-shifting approach designed for building foundation models in multi-physics scientific computing.

Zero-Shot Learning

Should We Respect LLMs? A Cross-Lingual Study on the Influence of Prompt Politeness on LLM Performance

no code implementations22 Feb 2024 Ziqi Yin, Hao Wang, Kaito Horio, Daisuke Kawahara, Satoshi Sekine

We investigate the impact of politeness levels in prompts on the performance of large language models (LLMs).

Large-scale Benchmarking of Metaphor-based Optimization Heuristics

no code implementations15 Feb 2024 Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck

The number of proposed iterative optimization heuristics is growing steadily, and with this growth, there have been many points of discussion within the wider community.

Benchmarking Experimental Design

A Factor Graph Model of Trust for a Collaborative Multi-Agent System

no code implementations10 Feb 2024 Behzad Akbari, Mingfeng Yuan, Hao Wang, Haibin Zhu, Jinjun Shan

In the field of Multi-Agent Systems (MAS), known for their openness, dynamism, and cooperative nature, the ability to trust the resources and services of other agents is crucial.

Bayesian Inference

Benchmarking Large Language Models on Communicative Medical Coaching: a Novel System and Dataset

no code implementations8 Feb 2024 Hengguan Huang, Songtao Wang, Hongfu Liu, Hao Wang, Ye Wang

To construct the ChatCoach system, we developed a dataset and integrated Large Language Models such as ChatGPT and Llama2, aiming to assess their effectiveness in communicative medical coaching tasks.

Benchmarking

The Future of Cognitive Strategy-enhanced Persuasive Dialogue Agents: New Perspectives and Trends

no code implementations7 Feb 2024 Mengqi Chen, Bin Guo, Hao Wang, Haoyu Li, Qian Zhao, Jingqi Liu, Yasan Ding, Yan Pan, Zhiwen Yu

To depict the research trends of CogAgent, in this paper, we first present several fundamental cognitive psychology theories and give the formalized definition of three typical cognitive strategies, including the persuasion strategy, the topic path planning strategy, and the argument structure prediction strategy.

Response Generation

Partially Recentralization Softmax Loss for Vision-Language Models Robustness

no code implementations6 Feb 2024 Hao Wang, Xin Zhang, JinZhe Jiang, YaQian Zhao, Chen Li

However, it has been shown that multimodal NLP are vulnerable to adversarial attacks, where the outputs of a model can be dramatically changed by a perturbation to the input.

Adversarial Robustness

Harnessing the Plug-and-Play Controller by Prompting

no code implementations6 Feb 2024 Hao Wang, Lei Sha

The proposed approach aims to enhance the fluency of generated text by guiding the generation process with PPCs.

Attribute Language Modelling +1

Understanding the planning of LLM agents: A survey

no code implementations5 Feb 2024 Xu Huang, Weiwen Liu, Xiaolong Chen, Xingmei Wang, Hao Wang, Defu Lian, Yasheng Wang, Ruiming Tang, Enhong Chen

As Large Language Models (LLMs) have shown significant intelligence, the progress to leverage LLMs as planning modules of autonomous agents has attracted more attention.

FreDF: Learning to Forecast in Frequency Domain

no code implementations4 Feb 2024 Hao Wang, Licheng Pan, Zhichao Chen, Degui Yang, Sen Zhang, Yifei Yang, Xinggao Liu, Haoxuan Li, DaCheng Tao

Time series modeling is uniquely challenged by the presence of autocorrelation in both historical and label sequences.

Time Series

Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical Guarantees

no code implementations3 Feb 2024 Guang-Yuan Hao, Hengguan Huang, Haotian Wang, Jie Gao, Hao Wang

In this paper, we propose the first general method, dubbed composite active learning (CAL), for multi-domain AL. Our approach explicitly considers the domain-level and instance-level information in the problem; CAL first assigns domain-level budgets according to domain-level importance, which is estimated by optimizing an upper error bound that we develop; with the domain-level budgets, CAL then leverages a certain instance-level query strategy to select samples to label from each domain.

Active Learning

Natural Counterfactuals With Necessary Backtracking

no code implementations2 Feb 2024 Guang-Yuan Hao, Jiji Zhang, Biwei Huang, Hao Wang, Kun Zhang

Counterfactual reasoning is pivotal in human cognition and especially important for providing explanations and making decisions.

counterfactual Counterfactual Reasoning

Formal-LLM: Integrating Formal Language and Natural Language for Controllable LLM-based Agents

1 code implementation1 Feb 2024 Zelong Li, Wenyue Hua, Hao Wang, He Zhu, Yongfeng Zhang

A stack-based LLM plan generation process is then conducted under the supervision of the automaton to ensure that the generated plan satisfies the constraints, making the planning process controllable.

Reconfigurable AI Modules Aided Channel Estimation and MIMO Detection

no code implementations29 Jan 2024 Xiangzhao Qin, Sha Hu, Jiankun Zhang, Jing Qian, Hao Wang

Deep learning (DL) based channel estimation (CE) and multiple input and multiple output detection (MIMODet), as two separate research topics, have provided convinced evidence to demonstrate the effectiveness and robustness of artificial intelligence (AI) for receiver design.

Super-Resolution

TransTroj: Transferable Backdoor Attacks to Pre-trained Models via Embedding Indistinguishability

1 code implementation29 Jan 2024 Hao Wang, Tao Xiang, Shangwei Guo, Jialing He, Hangcheng Liu, Tianwei Zhang

Adopting untrusted PTMs may suffer from backdoor attacks, where the adversary can compromise the downstream models by injecting backdoors into the PTM.

Backdoor Attack

Attentive Convolutional Deep Reinforcement Learning for Optimizing Solar-Storage Systems in Real-Time Electricity Markets

no code implementations29 Jan 2024 Jinhao Li, Changlong Wang, Hao Wang

This paper studies the synergy of solar-battery energy storage system (BESS) and develops a viable strategy for the BESS to unlock its economic potential by serving as a backup to reduce solar curtailments while also participating in the electricity market.

Learning to Trust Your Feelings: Leveraging Self-awareness in LLMs for Hallucination Mitigation

no code implementations27 Jan 2024 Yuxin Liang, Zhuoyang Song, Hao Wang, Jiaxing Zhang

We evaluate the ability of Large Language Models (LLMs) to discern and express their internal knowledge state, a key factor in countering factual hallucination and ensuring reliable application of LLMs.

Hallucination Knowledge Probing +1

Driving Towards Inclusion: Revisiting In-Vehicle Interaction in Autonomous Vehicles

no code implementations26 Jan 2024 Ashish Bastola, Julian Brinkley, Hao Wang, Abolfazl Razi

This paper presents a comprehensive literature review of the current state of in-vehicle human-computer interaction (HCI) in the context of self-driving vehicles, with a specific focus on inclusion and accessibility.

Autonomous Vehicles

Hierarchical Continual Reinforcement Learning via Large Language Model

no code implementations25 Jan 2024 Chaofan Pan, Xin Yang, Hao Wang, Wei Wei, Tianrui Li

Despite the progress in continual reinforcement learning (CRL), existing methods often suffer from insufficient knowledge transfer, particularly when the tasks are diverse.

Language Modelling Large Language Model +3

Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations

1 code implementation25 Jan 2024 Xinyue Xu, Yi Qin, Lu Mi, Hao Wang, Xiaomeng Li

Our ECBMs address both limitations of existing CBMs, providing higher accuracy and richer concept interpretations.

Style-Consistent 3D Indoor Scene Synthesis with Decoupled Objects

no code implementations24 Jan 2024 Yunfan Zhang, Hong Huang, Zhiwei Xiong, Zhiqi Shen, Guosheng Lin, Hao Wang, Nicholas Vun

The core strength of our pipeline lies in its ability to generate 3D scenes that are not only visually impressive but also exhibit features like photorealism, multi-view consistency, and diversity.

Indoor Scene Synthesis

EndoGaussians: Single View Dynamic Gaussian Splatting for Deformable Endoscopic Tissues Reconstruction

no code implementations24 Jan 2024 Yangsen Chen, Hao Wang

The accurate 3D reconstruction of deformable soft body tissues from endoscopic videos is a pivotal challenge in medical applications such as VR surgery and medical image analysis.

3D Reconstruction

Raidar: geneRative AI Detection viA Rewriting

1 code implementation23 Jan 2024 Chengzhi Mao, Carl Vondrick, Hao Wang, Junfeng Yang

We find that large language models (LLMs) are more likely to modify human-written text than AI-generated text when tasked with rewriting.

SlideAVSR: A Dataset of Paper Explanation Videos for Audio-Visual Speech Recognition

no code implementations18 Jan 2024 Hao Wang, Shuhei Kurita, Shuichiro Shimizu, Daisuke Kawahara

Audio-visual speech recognition (AVSR) is a multimodal extension of automatic speech recognition (ASR), using video as a complement to audio.

Audio-Visual Speech Recognition Automatic Speech Recognition +4

CycLight: learning traffic signal cooperation with a cycle-level strategy

no code implementations16 Jan 2024 Gengyue Han, Xiaohan Liu, Xianyue Peng, Hao Wang, Yu Han

This study introduces CycLight, a novel cycle-level deep reinforcement learning (RL) approach for network-level adaptive traffic signal control (NATSC) systems.

Decision Making Reinforcement Learning (RL)

HiBid: A Cross-Channel Constrained Bidding System with Budget Allocation by Hierarchical Offline Deep Reinforcement Learning

no code implementations29 Dec 2023 Hao Wang, Bo Tang, Chi Harold Liu, Shangqin Mao, Jiahong Zhou, Zipeng Dai, Yaqi Sun, Qianlong Xie, Xingxing Wang, Dong Wang

Online display advertising platforms service numerous advertisers by providing real-time bidding (RTB) for the scale of billions of ad requests every day.

Data Augmentation

Federated Continual Learning via Knowledge Fusion: A Survey

no code implementations27 Dec 2023 Xin Yang, Hao Yu, Xin Gao, Hao Wang, Junbo Zhang, Tianrui Li

The key objective of FCL is to fuse heterogeneous knowledge from different clients and retain knowledge of previous tasks while learning on new ones.

Continual Learning Federated Learning

Word length-aware text spotting: Enhancing detection and recognition in dense text image

no code implementations25 Dec 2023 Hao Wang, Huabing Zhou, Yanduo Zhang, Tao Lu, Jiayi Ma

Scene text spotting is essential in various computer vision applications, enabling extracting and interpreting textual information from images.

Text Detection Text Spotting

LARP: Language-Agent Role Play for Open-World Games

no code implementations24 Dec 2023 Ming Yan, Ruihao Li, Hao Zhang, Hao Wang, Zhilan Yang, Ji Yan

Language agents have shown impressive problem-solving skills within defined settings and brief timelines.

Decision Making

A Novel Field-Free SOT Magnetic Tunnel Junction With Local VCMA-Induced Switching

no code implementations24 Dec 2023 Rui Zhou, Haiyang Zhang, Hao Wang, Jin He, Qijun Huang, Sheng Chang

By integrating the local voltage-controlled magnetic anisotropy (VCMA) effect, Dzyaloshinskii-Moriya interaction (DMI) effect, and spin-orbit torque (SOT) effect, we propose a novel device structure for field-free magnetic tunnel junction (MTJ).

BrainVis: Exploring the Bridge between Brain and Visual Signals via Image Reconstruction

no code implementations22 Dec 2023 Honghao Fu, Zhiqi Shen, Jing Jih Chin, Hao Wang

This leads to substantial limitations in existing works of visual stimuli reconstruction from EEG, such as difficulties in aligning EEG embeddings with the fine-grained semantic information and a heavy reliance on additional large self-collected dataset for training.

EEG Image Reconstruction

Learning to Prompt Knowledge Transfer for Open-World Continual Learning

no code implementations22 Dec 2023 Yujie Li, Xin Yang, Hao Wang, Xiangkun Wang, Tianrui Li

This paper studies the problem of continual learning in an open-world scenario, referred to as Open-world Continual Learning (OwCL).

Continual Learning Transfer Learning

SkyMask: Attack-agnostic Robust Federated Learning with Fine-grained Learnable Masks

no code implementations19 Dec 2023 Peishen Yan, Hao Wang, Tao Song, Yang Hua, Ruhui Ma, Ningxin Hu, Mohammad R. Haghighat, Haibing Guan

Specifically, the FL server applies parameter-level masks to model updates uploaded by clients and trains the masks over a small clean dataset (i. e., root dataset) to learn the subtle difference between benign and malicious model updates in a high-dimension space.

Federated Learning

The Fallacy of Borda Count Method -- Why it is Useless with Group Intelligence and Shouldn't be Used with Big Data including Banking Customer Services

no code implementations16 Dec 2023 Hao Wang

In this paper, we rely on the theory developed by Wang from 2021 to 2023 to demonstrate that online cultural rating platform rating data often evolve into Poisson/Pareto behavior, and individualistic voting preferences are predictable without any data input, so Borda Count Method (or, Range Voting Method) has intrinsic fallacy and should not be used as a voting theory method.

Fractional Deep Reinforcement Learning for Age-Minimal Mobile Edge Computing

no code implementations16 Dec 2023 Lyudong Jin, Ming Tang, Meng Zhang, Hao Wang

The uncertain edge load dynamics, the nature of the fractional objective, and hybrid continuous-discrete action space (due to the joint optimization) make this problem challenging and existing approaches not directly applicable.

Autonomous Driving Edge-computing +3

Large Foundation Models for Power Systems

1 code implementation12 Dec 2023 Chenghao Huang, Siyang Li, Ruohong Liu, Hao Wang, Yize Chen

Foundation models, such as Large Language Models (LLMs), can respond to a wide range of format-free queries without any task-specific data collection or model training, creating various research and application opportunities for the modeling and operation of large-scale power systems.

Retrieval Scheduling

PFLlib: Personalized Federated Learning Algorithm Library

1 code implementation8 Dec 2023 Jianqing Zhang, Yang Liu, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Jian Cao

Amid the ongoing advancements in Federated Learning (FL), a machine learning paradigm that allows collaborative learning with data privacy protection, personalized FL (pFL) has gained significant prominence as a research direction within the FL domain.

Personalized Federated Learning

DBCopilot: Scaling Natural Language Querying to Massive Databases

1 code implementation6 Dec 2023 Tianshu Wang, Hongyu Lin, Xianpei Han, Le Sun, Xiaoyang Chen, Hao Wang, Zhenyu Zeng

Text-to-SQL simplifies database interactions by enabling non-experts to convert their natural language (NL) questions into Structured Query Language (SQL) queries.

Navigate Question Generation +2

Non-Intrusive Load Monitoring for Feeder-Level EV Charging Detection: Sliding Window-based Approaches to Offline and Online Detection

no code implementations4 Dec 2023 Cameron Martin, Fucai Ke, Hao Wang

Our experimental results demonstrate high-accuracy EV charging detection at the feeder level, achieving an F-Score of 98. 88% in offline detection and 93. 01% in online detection.

Management Non-Intrusive Load Monitoring

Deep Reinforcement Learning for Community Battery Scheduling under Uncertainties of Load, PV Generation, and Energy Prices

no code implementations4 Dec 2023 Jiarong Fan, Hao Wang

In response to the growing uptake of distributed energy resources (DERs), community batteries have emerged as a promising solution to support renewable energy integration, reduce peak load, and enhance grid reliability.

Reinforcement Learning (RL) Scheduling

PAC Privacy Preserving Diffusion Models

no code implementations2 Dec 2023 Qipan Xu, Youlong Ding, Jie Gao, Hao Wang

Data privacy protection is garnering increased attention among researchers.

Privacy Preserving

Quantum Langevin Dynamics for Optimization

no code implementations27 Nov 2023 Zherui Chen, Yuchen Lu, Hao Wang, Yizhou Liu, Tongyang Li

Finally, based on the observations when comparing QLD with classical Fokker-Plank-Smoluchowski equation, we propose a time-dependent QLD by making temperature and $\hbar$ time-dependent parameters, which can be theoretically proven to converge better than the time-independent case and also outperforms a series of state-of-the-art quantum and classical optimization algorithms in many non-convex landscapes.

How Far Have We Gone in Vulnerability Detection Using Large Language Models

1 code implementation21 Nov 2023 Zeyu Gao, Hao Wang, Yuchen Zhou, Wenyu Zhu, Chao Zhang

Given the significant successes of large language models (LLMs) in various tasks, there is growing anticipation of their efficacy in vulnerability detection.

Vulnerability Detection

On the Noise Scheduling for Generating Plausible Designs with Diffusion Models

no code implementations19 Nov 2023 Jiajie Fan, Laure Vuaille, Thomas Bäck, Hao Wang

We delve into the impact of noise schedules of diffusion models on the plausibility of the outcome: there exists a range of noise levels at which the model's performance decides the result plausibility.

Scheduling

Enhancing Recommender System Performance by Histogram Equalization

no code implementations15 Nov 2023 Hao Wang

As a preprocessing step to recommender system algorithms, histogram equalization could enhance both the accuracy and fairness metrics of the recommender system algorithms.

Fairness Recommendation Systems

SCAAT: Improving Neural Network Interpretability via Saliency Constrained Adaptive Adversarial Training

no code implementations9 Nov 2023 Rui Xu, Wenkang Qin, Peixiang Huang, Hao Wang, Lin Luo

Deep Neural Networks (DNNs) are expected to provide explanation for users to understand their black-box predictions.

APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation

1 code implementation6 Nov 2023 Mingjia Yin, Hao Wang, Xiang Xu, Likang Wu, Sirui Zhao, Wei Guo, Yong liu, Ruiming Tang, Defu Lian, Enhong Chen

To this end, we propose a graph-driven framework, named Adaptive and Personalized Graph Learning for Sequential Recommendation (APGL4SR), that incorporates adaptive and personalized global collaborative information into sequential recommendation systems.

Graph Learning Multi-Task Learning +1

ProAgent: From Robotic Process Automation to Agentic Process Automation

1 code implementation2 Nov 2023 Yining Ye, Xin Cong, Shizuo Tian, Jiannan Cao, Hao Wang, Yujia Qin, Yaxi Lu, Heyang Yu, Huadong Wang, Yankai Lin, Zhiyuan Liu, Maosong Sun

Empirical experiments are conducted to detail its construction and execution procedure of workflow, showcasing the feasibility of APA, unveiling the possibility of a new paradigm of automation driven by agents.

Decision Making

Pre-trained Recommender Systems: A Causal Debiasing Perspective

1 code implementation30 Oct 2023 Ziqian Lin, Hao Ding, Nghia Trong Hoang, Branislav Kveton, Anoop Deoras, Hao Wang

In particular, we propose to develop a generic recommender that captures universal interaction patterns by training on generic user-item interaction data extracted from different domains, which can then be fast adapted to improve few-shot learning performance in unseen new domains (with limited data).

Few-Shot Learning Recommendation Systems

Is Human Culture Locked by Evolution?

no code implementations28 Oct 2023 Hao Wang

Human culture has evolved for thousands of years and thrived in the era of Internet.

Recommendation Systems

Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning

no code implementations24 Oct 2023 Yuxiang Wang, Xiao Yan, Chuang Hu, Fangcheng Fu, Wentao Zhang, Hao Wang, Shuo Shang, Jiawei Jiang

For graph self-supervised learning (GSSL), masked autoencoder (MAE) follows the generative paradigm and learns to reconstruct masked graph edges or node features.

Contrastive Learning Graph Classification +4

Woodpecker: Hallucination Correction for Multimodal Large Language Models

1 code implementation24 Oct 2023 Shukang Yin, Chaoyou Fu, Sirui Zhao, Tong Xu, Hao Wang, Dianbo Sui, Yunhang Shen, Ke Li, Xing Sun, Enhong Chen

Hallucination is a big shadow hanging over the rapidly evolving Multimodal Large Language Models (MLLMs), referring to the phenomenon that the generated text is inconsistent with the image content.

Hallucination

DocTrack: A Visually-Rich Document Dataset Really Aligned with Human Eye Movement for Machine Reading

1 code implementation23 Oct 2023 Hao Wang, Qingxuan Wang, Yue Li, Changqing Wang, Chenhui Chu, Rui Wang

The use of visually-rich documents (VRDs) in various fields has created a demand for Document AI models that can read and comprehend documents like humans, which requires the overcoming of technical, linguistic, and cognitive barriers.

document understanding Reading Comprehension

Vision-Enhanced Semantic Entity Recognition in Document Images via Visually-Asymmetric Consistency Learning

no code implementations23 Oct 2023 Hao Wang, Xiahua Chen, Rui Wang, Chenhui Chu

Extracting meaningful entities belonging to predefined categories from Visually-rich Form-like Documents (VFDs) is a challenging task.

LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay

1 code implementation23 Oct 2023 Yihuai Lan, Zhiqiang Hu, Lei Wang, Yang Wang, Deheng Ye, Peilin Zhao, Ee-Peng Lim, Hui Xiong, Hao Wang

To achieve this goal, we adopt Avalon, a representative communication game, as the environment and use system prompts to guide LLM agents to play the game.

A Data-Centric Multi-Objective Learning Framework for Responsible Recommendation Systems

no code implementations20 Oct 2023 Xu Huang, Jianxun Lian, Hao Wang, Defu Lian, Xing Xie

Recommendation systems effectively guide users in locating their desired information within extensive content repositories.

Fairness Recommendation Systems

Fact-based Agent modeling for Multi-Agent Reinforcement Learning

no code implementations18 Oct 2023 Baofu Fang, Caiming Zheng, Hao Wang

To eliminate this assumption and achieve agent modeling in unknown scenarios, Fact-based Agent modeling (FAM) method is proposed in which fact-based belief inference (FBI) network models other agents in partially observable environment only based on its local information.

Federated Learning Multi-agent Reinforcement Learning +1

Combat Urban Congestion via Collaboration: Heterogeneous GNN-based MARL for Coordinated Platooning and Traffic Signal Control

no code implementations17 Oct 2023 Xianyue Peng, Hang Gao, Hao Wang, H. Michael Zhang

Over the years, reinforcement learning has emerged as a popular approach to develop signal control and vehicle platooning strategies either independently or in a hierarchical way.

Multi-agent Reinforcement Learning reinforcement-learning

Joint Optimization of Traffic Signal Control and Vehicle Routing in Signalized Road Networks using Multi-Agent Deep Reinforcement Learning

no code implementations16 Oct 2023 Xianyue Peng, Hang Gao, Gengyue Han, Hao Wang, Michael Zhang

In this paper, we propose a joint optimization approach for traffic signal control and vehicle routing in signalized road networks.

Private Synthetic Data Meets Ensemble Learning

no code implementations15 Oct 2023 Haoyuan Sun, Navid Azizan, Akash Srivastava, Hao Wang

When machine learning models are trained on synthetic data and then deployed on real data, there is often a performance drop due to the distribution shift between synthetic and real data.

Ensemble Learning

B-Spine: Learning B-Spline Curve Representation for Robust and Interpretable Spinal Curvature Estimation

no code implementations14 Oct 2023 Hao Wang, Qiang Song, Ruofeng Yin, Rui Ma, Yizhou Yu, Yi Chang

In this paper, we propose B-Spine, a novel deep learning pipeline to learn B-spline curve representation of the spine and estimate the Cobb angles for spinal curvature estimation from low-quality X-ray images.

Image-to-Image Translation

Continuous Invariance Learning

no code implementations9 Oct 2023 Yong Lin, Fan Zhou, Lu Tan, Lintao Ma, Jiameng Liu, Yansu He, Yuan Yuan, Yu Liu, James Zhang, Yujiu Yang, Hao Wang

To address this challenge, we then propose Continuous Invariance Learning (CIL), which extracts invariant features across continuously indexed domains.

Cloud Computing

LAiW: A Chinese Legal Large Language Models Benchmark

1 code implementation9 Oct 2023 Yongfu Dai, Duanyu Feng, Jimin Huang, Haochen Jia, Qianqian Xie, Yifang Zhang, Weiguang Han, Wei Tian, Hao Wang

Through automated evaluation of current general and legal domain LLMs on our benchmark, we indicate that these LLMs may not align with the logic of legal practice.

Information Retrieval

Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language Models

1 code implementation1 Oct 2023 Duanyu Feng, Yongfu Dai, Jimin Huang, Yifang Zhang, Qianqian Xie, Weiguang Han, Zhengyu Chen, Alejandro Lopez-Lira, Hao Wang

We then propose the first Credit and Risk Assessment Large Language Model (CALM) by instruction tuning, tailored to the nuanced demands of various financial risk assessment tasks.

Decision Making Language Modelling +1

LatticeGen: A Cooperative Framework which Hides Generated Text in a Lattice for Privacy-Aware Generation on Cloud

no code implementations29 Sep 2023 Mengke Zhang, Tianxing He, Tianle Wang, Lu Mi, FatemehSadat Mireshghallah, Binyi Chen, Hao Wang, Yulia Tsvetkov

In the current user-server interaction paradigm of prompted generation with large language models (LLM) on cloud, the server fully controls the generation process, which leaves zero options for users who want to keep the generated text to themselves.

Deep Learning-Based Connector Detection for Robotized Assembly of Automotive Wire Harnesses

no code implementations24 Sep 2023 Hao Wang, Björn Johansson

The mating of connectors is essential in the final assembly of automotive wire harnesses due to the importance of connectors on wire harness connection and signal transmission.

Autonomous Driving object-detection +1

A Systematic Literature Review of Computer Vision Applications in Robotized Wire Harness Assembly

no code implementations24 Sep 2023 Hao Wang, Omkar Salunkhe, Walter Quadrini, Björn Johansson, Dan Lämkull, Fredrik Ore, Mélanie Despeisse, Luca Fumagalli, Johan Stahre

This article presents a systematic literature review on computer vision applications that have been proposed for robotized wire harness assembly, derives challenges from existing studies, and identifies opportunities for future research to promote a more practical robotized assembly of wire harnesses.

Overview of Computer Vision Techniques in Robotized Wire Harness Assembly: Current State and Future Opportunities

no code implementations24 Sep 2023 Hao Wang, Omkar Salunkhe, Walter Quadrini, Dan Lämkull, Fredrik Ore, Björn Johansson, Johan Stahre

This paradigm shift places more demand on automotive wire harnesses from the safety perspective and stresses the greater importance of high-quality wire harness assembly in vehicles.

Autonomous Driving

Monotonic Neural Ordinary Differential Equation: Time-series Forecasting for Cumulative Data

no code implementations23 Sep 2023 Zhichao Chen, Leilei Ding, Zhixuan Chu, Yucheng Qi, Jianmin Huang, Hao Wang

Time-Series Forecasting based on Cumulative Data (TSFCD) is a crucial problem in decision-making across various industrial scenarios.

Decision Making Time Series +1

SPGM: Prioritizing Local Features for enhanced speech separation performance

1 code implementation22 Sep 2023 Jia Qi Yip, Shengkui Zhao, Yukun Ma, Chongjia Ni, Chong Zhang, Hao Wang, Trung Hieu Nguyen, Kun Zhou, Dianwen Ng, Eng Siong Chng, Bin Ma

Dual-path is a popular architecture for speech separation models (e. g. Sepformer) which splits long sequences into overlapping chunks for its intra- and inter-blocks that separately model intra-chunk local features and inter-chunk global relationships.

Speech Separation

Collaborative Three-Stream Transformers for Video Captioning

no code implementations18 Sep 2023 Hao Wang, Libo Zhang, Heng Fan, Tiejian Luo

Meanwhile, we propose a cross-granularity attention module to align the interactions modeled by the three branches of transformers, then the three branches of transformers can support each other to exploit the most discriminative semantic information of different granularities for accurate predictions of captions.

Sentence Video Captioning

Community Battery Energy Storage Systems for Enhancing Distribution System Operation: A Multi-objective Optimization Approach

no code implementations5 Sep 2023 Yunqi Wang, Hao Wang, Markus Wagner, Ariel Liebman

The results show significant improvements in voltage regulation and DER utilization, demonstrating the potential of C-BESS in enabling more reliable DN operation.

MARL for Decentralized Electric Vehicle Charging Coordination with V2V Energy Exchange

no code implementations27 Aug 2023 Jiarong Fan, Hao Wang, Ariel Liebman

This paper addresses the EV charging coordination by considering vehicle-to-vehicle (V2V) energy exchange as the flexibility to harness in EV charging stations.

energy management Fairness +2

Cross-Entropy-Based Approach to Multi-Objective Electric Vehicle Charging Infrastructure Planning

no code implementations27 Aug 2023 Jinhao Li, Yu Hui Yuan, Qiushi Cui, Hao Wang

Therefore, we are motivated to develop a comprehensive multi-objective framework for optimal CS placement in a traffic network overlaid by a distribution network, considering multiple stakeholders' interested factors, such as traffic flow, PEV charging time cost, PEV travel distance, and the reliability of the distribution network.

Decision Making

Hybrid Transformer-RNN Architecture for Household Occupancy Detection Using Low-Resolution Smart Meter Data

no code implementations27 Aug 2023 Xinyu Liang, Hao Wang

Residential occupancy detection has become an enabling technology in today's urbanized world for various smart home applications, such as building automation, energy management, and improved security and comfort.

energy management Management

Multi-stage feature decorrelation constraints for improving CNN classification performance

1 code implementation24 Aug 2023 Qiuyu Zhu, Hao Wang, Xuewen Zu, Chengfei Liu

Considering that there are many layers in CNN, through experimental comparison and analysis, MFD Loss acts on multiple front layers of CNN, constrains the output features of each layer and each channel, and performs supervision training jointly with classification loss function during network training.

kTrans: Knowledge-Aware Transformer for Binary Code Embedding

1 code implementation24 Aug 2023 Wenyu Zhu, Hao Wang, Yuchen Zhou, JiaMing Wang, Zihan Sha, Zeyu Gao, Chao Zhang

By feeding explicit knowledge as additional inputs to the Transformer, and fusing implicit knowledge with a novel pre-training task, kTrans provides a new perspective to incorporating domain knowledge into a Transformer framework.

Outlier Detection

ChatHaruhi: Reviving Anime Character in Reality via Large Language Model

1 code implementation18 Aug 2023 Cheng Li, Ziang Leng, Chenxi Yan, Junyi Shen, Hao Wang, Weishi MI, Yaying Fei, Xiaoyang Feng, Song Yan, HaoSheng Wang, Linkang Zhan, Yaokai Jia, Pingyu Wu, Haozhen Sun

Role-playing chatbots built on large language models have drawn interest, but better techniques are needed to enable mimicking specific fictional characters.

Language Modelling Large Language Model +2

KMF: Knowledge-Aware Multi-Faceted Representation Learning for Zero-Shot Node Classification

no code implementations15 Aug 2023 Likang Wu, Junji Jiang, Hongke Zhao, Hao Wang, Defu Lian, Mengdi Zhang, Enhong Chen

However, the multi-faceted semantic orientation in the feature-semantic alignment has been neglected by previous work, i. e. the content of a node usually covers diverse topics that are relevant to the semantics of multiple labels.

Node Classification Representation Learning +1

Methods for Acquiring and Incorporating Knowledge into Stock Price Prediction: A Survey

no code implementations9 Aug 2023 Liping Wang, Jiawei Li, Lifan Zhao, Zhizhuo Kou, Xiaohan Wang, Xinyi Zhu, Hao Wang, Yanyan Shen, Lei Chen

Predicting stock prices presents a challenging research problem due to the inherent volatility and non-linear nature of the stock market.

Stock Price Prediction

Backdoor Federated Learning by Poisoning Backdoor-Critical Layers

no code implementations8 Aug 2023 Haomin Zhuang, Mingxian Yu, Hao Wang, Yang Hua, Jian Li, Xu Yuan

Federated learning (FL) has been widely deployed to enable machine learning training on sensitive data across distributed devices.

Backdoor Attack Federated Learning

ConvFormer: Revisiting Transformer for Sequential User Modeling

no code implementations5 Aug 2023 Hao Wang, Jianxun Lian, Mingqi Wu, Haoxuan Li, Jiajun Fan, Wanyue Xu, Chaozhuo Li, Xing Xie

Sequential user modeling, a critical task in personalized recommender systems, focuses on predicting the next item a user would prefer, requiring a deep understanding of user behavior sequences.

Recommendation Systems

MFMAN-YOLO: A Method for Detecting Pole-like Obstacles in Complex Environment

no code implementations24 Jul 2023 Lei Cai, Hao Wang, Congling Zhou, Yongqiang Wang, Boyu Liu

To solve the problem that the feature information of pole-like obstacles in complex environments is easily lost, resulting in low detection accuracy and low real-time performance, a multi-scale hybrid attention mechanism detection algorithm is proposed in this paper.

A Good Student is Cooperative and Reliable: CNN-Transformer Collaborative Learning for Semantic Segmentation

no code implementations ICCV 2023 Jinjing Zhu, Yunhao Luo, Xu Zheng, Hao Wang, Lin Wang

In this paper, we strive to answer the question "how to collaboratively learn convolutional neural network (CNN)-based and vision transformer (ViT)-based models by selecting and exchanging the reliable knowledge between them for semantic segmentation?"

Knowledge Distillation Semantic Segmentation

Adversarial Latent Autoencoder with Self-Attention for Structural Image Synthesis

no code implementations19 Jul 2023 Jiajie Fan, Laure Vuaille, Hao Wang, Thomas Bäck

The potential of SA-ALAE is shown by generating engineering blueprints in a real automotive design task.

Image Generation

PreDiff: Precipitation Nowcasting with Latent Diffusion Models

1 code implementation NeurIPS 2023 Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle Maddix, Yi Zhu, Mu Li, Yuyang Wang

We conduct empirical studies on two datasets: N-body MNIST, a synthetic dataset with chaotic behavior, and SEVIR, a real-world precipitation nowcasting dataset.

Denoising

Local Conditional Neural Fields for Versatile and Generalizable Large-Scale Reconstructions in Computational Imaging

1 code implementation12 Jul 2023 Hao Wang, Jiabei Zhu, Yunzhe Li, QianWan Yang, Lei Tian

Unlike traditional neural fields frameworks, LCNF incorporates a local conditional representation that promotes model generalization, learning multiscale information, and efficient processing of large-scale imaging data.

Image Reconstruction Super-Resolution

LogitMat : Zeroshot Learning Algorithm for Recommender Systems without Transfer Learning or Pretrained Models

no code implementations6 Jul 2023 Hao Wang

Unlike other sectors such as fraud detection in the Fintech industry, recommender system is both deep and broad.

Fraud Detection Meta-Learning +2

Optimal Bandwidth Selection for DENCLUE Algorithm

no code implementations6 Jul 2023 Hao Wang

In 2007, a density-based clustering algorithm named DENCLUE was invented to solve clustering problem for nonlinear data structures.

Clustering

FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy

3 code implementations1 Jul 2023 Jianqing Zhang, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan

To address this, we propose the Federated Conditional Policy (FedCP) method, which generates a conditional policy for each sample to separate the global information and personalized information in its features and then processes them by a global head and a personalized head, respectively.

Personalized Federated Learning

Counterfactual Collaborative Reasoning

no code implementations30 Jun 2023 Jianchao Ji, Zelong Li, Shuyuan Xu, Max Xiong, Juntao Tan, Yingqiang Ge, Hao Wang, Yongfeng Zhang

In this paper, we explore how the two reasoning abilities can be jointly modeled to enhance both accuracy and explainability of machine learning models.

counterfactual Counterfactual Reasoning +3

PMaF: Deep Declarative Layers for Principal Matrix Features

1 code implementation26 Jun 2023 Zhiwei Xu, Hao Wang, Yanbin Liu, Stephen Gould

We explore two differentiable deep declarative layers, namely least squares on sphere (LESS) and implicit eigen decomposition (IED), for learning the principal matrix features (PMaF).

Energy Optimization for HVAC Systems in Multi-VAV Open Offices: A Deep Reinforcement Learning Approach

2 code implementations23 Jun 2023 Hao Wang, Xiwen Chen, Natan Vital, Edward. Duffy, Abolfazl Razi

It takes only a total of 40 minutes for 5 epochs (about 7. 75 minutes per epoch) to train a network with superior performance and covering diverse conditions for its low-complexity architecture; therefore, it easily adapts to changes in the building setups, weather conditions, occupancy rate, etc.

energy management Total Energy

Taxonomy-Structured Domain Adaptation

1 code implementation13 Jun 2023 Tianyi Liu, Zihao Xu, Hao He, Guang-Yuan Hao, Guang-He Lee, Hao Wang

Domain adaptation aims to mitigate distribution shifts among different domains.

Domain Adaptation

Skellam Rank: Fair Learning to Rank Algorithm Based on Poisson Process and Skellam Distribution for Recommender Systems

no code implementations11 Jun 2023 Hao Wang

In this paper, we propose a fair recommender system algorithm that uses Poisson process and Skellam distribution.

Fairness Learning-To-Rank +2

Self-Interpretable Time Series Prediction with Counterfactual Explanations

no code implementations9 Jun 2023 Jingquan Yan, Hao Wang

Interpretable time series prediction is crucial for safety-critical areas such as healthcare and autonomous driving.

Autonomous Driving counterfactual +3

A Peer-to-peer Federated Continual Learning Network for Improving CT Imaging from Multiple Institutions

no code implementations3 Jun 2023 Hao Wang, Ruihong He, XiaoYu Zhang, Zhaoying Bian, Dong Zeng, Jianhua Ma

In this work, we propose a novel peer-to-peer federated continual learning strategy to improve low-dose CT imaging performance from multiple institutions.

Computed Tomography (CT) Continual Learning +1

Representation Reliability and Its Impact on Downstream Tasks

no code implementations31 May 2023 Young-Jin Park, Hao Wang, Shervin Ardeshir, Navid Azizan

Self-supervised pre-trained models extract general-purpose representations from data, and quantifying how reliable they are is crucial because many downstream models use these representations as input for their own tasks.

Uncertainty Quantification

A Survey on Large Language Models for Recommendation

1 code implementation31 May 2023 Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, HengShu Zhu, Qi Liu, Hui Xiong, Enhong Chen

Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recommendation Systems (RS).

Recommendation Systems Self-Supervised Learning

DPFormer: Learning Differentially Private Transformer on Long-Tailed Data

no code implementations28 May 2023 Youlong Ding, Xueyang Wu, Hao Wang, Weike Pan

The Transformer has emerged as a versatile and effective architecture with broad applications.

Modeling Task Relationships in Multi-variate Soft Sensor with Balanced Mixture-of-Experts

no code implementations25 May 2023 Yuxin Huang, Hao Wang, Zhaoran Liu, Licheng Pan, Haozhe Li, Xinggao Liu

Accurate estimation of multiple quality variables is critical for building industrial soft sensor models, which have long been confronted with data efficiency and negative transfer issues.

Two-Bit RIS-Aided Communications at 3.5GHz: Some Insights from the Measurement Results Under Multiple Practical Scenes

no code implementations19 May 2023 Shun Zhang, Haoran Sun, Runze Yu, Hongshenyuan Cui, Jian Ren, Feifei Gao, Shi Jin, Hongxiang Xie, Hao Wang

In particular, we adopt a self-developed broadband intelligent communication system 40MHz-Net (BICT-40N) terminal in order to fully acquire the channel information.

Intelligent Communication Quantization

MaGIC: Multi-modality Guided Image Completion

no code implementations19 May 2023 Yongsheng Yu, Hao Wang, Tiejian Luo, Heng Fan, Libo Zhang

In this paper, we propose a novel, simple yet effective method for Multi-modal Guided Image Completion, dubbed MaGIC, which not only supports a wide range of single modality as the guidance (e. g., text, canny edge, sketch, segmentation, depth, and pose), but also adapts to arbitrarily customized combination of these modalities (i. e., arbitrary multi-modality) for image completion.

Self-discipline on multiple channels

1 code implementation27 Apr 2023 Jiutian Zhao, Liang Luo, Hao Wang

Comparative experimental results on both datasets show that SMC-2 outperforms Label Smoothing Regularizaion and Self-distillation From The Last Mini-batch on all models, and outperforms the state-of-the-art Sharpness-Aware Minimization method on 83% of the models. Compatibility of SMC-2 and data augmentation experimental results show that using both SMC-2 and data augmentation improves the generalization ability of the model between 0. 28% and 1. 80% compared to using only data augmentation.

Data Augmentation

Optimal Energy Storage Scheduling for Wind Curtailment Reduction and Energy Arbitrage: A Deep Reinforcement Learning Approach

no code implementations5 Apr 2023 Jinhao Li, Changlong Wang, Hao Wang

However, the variable nature of wind generation can undermine system reliability and lead to wind curtailment, causing substantial economic losses to wind power producers.

Scheduling

Fairness-Aware Optimization of Vehicle-to-Vehicle Interaction for Smart EV Charging Coordination

no code implementations5 Apr 2023 Aditya Khele, Canchen Jiang, Hao Wang

We formulate a cost minimization problem for an EV charging station to optimize the V2V schedule together with vehicle-to-grid (V2G), grid-to-vehicle (G2V) charging, as well as the use of renewable energy.

Fairness

Analysis and Visualization of the Parameter Space of Matrix Factorization-based Recommender Systems

no code implementations25 Mar 2023 Hao Wang

We continue the research in this direction in this paper, and visualize the inner structure of the parameter space of matrix factorization technologies.

Recommendation Systems

Evolution of the Online Rating Platform Data Structures and its Implications for Recommender Systems

no code implementations25 Mar 2023 Hao Wang

Understanding the evolution pattern and its underlying mechanism is the key to understand the structures of input data for recommender systems.

Recommendation Systems

TAPS3D: Text-Guided 3D Textured Shape Generation from Pseudo Supervision

1 code implementation CVPR 2023 Jiacheng Wei, Hao Wang, Jiashi Feng, Guosheng Lin, Kim-Hui Yap

We conduct extensive experiments to analyze each of our proposed components and show the efficacy of our framework in generating high-fidelity 3D textured and text-relevant shapes.

Distribution-restrained Softmax Loss for the Model Robustness

no code implementations22 Mar 2023 Hao Wang, Chen Li, JinZhe Jiang, Xin Zhang, YaQian Zhao, Weifeng Gong

Recently, the robustness of deep learning models has received widespread attention, and various methods for improving model robustness have been proposed, including adversarial training, model architecture modification, design of loss functions, certified defenses, and so on.

A Dual-branch Self-supervised Representation Learning Framework for Tumour Segmentation in Whole Slide Images

no code implementations20 Mar 2023 Hao Wang, Euijoon Ahn, Jinman Kim

These SSL approaches, however, are not designed for handling multi-resolution WSIs, which limits their performance in learning discriminative image features.

Representation Learning Self-Supervised Learning +1

Enhancing Text Generation with Cooperative Training

1 code implementation16 Mar 2023 Tong Wu, Hao Wang, Zhongshen Zeng, Wei Wang, Hai-Tao Zheng, Jiaxing Zhang

Recently, there has been a surge in the use of generated data to enhance the performance of downstream models, largely due to the advancements in pre-trained language models.

MRPC QQP +2

Betti Number for Point Sets

no code implementations11 Mar 2023 Hao Wang

Topology is the foundation for many industrial applications ranging from CAD to simulation analysis.

PowerMat: context-aware recommender system without user item rating values that solves the cold-start problem

no code implementations11 Mar 2023 Hao Wang

One important sub-field of recommender systems that has been stagnating is context-aware recommender systems.

Recommendation Systems

Kernel-CF: Collaborative filtering done right with social network analysis and kernel smoothing

no code implementations8 Mar 2023 Hao Wang

Collaborative filtering is the simplest but oldest machine learning algorithm in the field of recommender systems.

Collaborative Filtering Recommendation Systems

GUESR: A Global Unsupervised Data-Enhancement with Bucket-Cluster Sampling for Sequential Recommendation

no code implementations1 Mar 2023 Yongqiang Han, Likang Wu, Hao Wang, Guifeng Wang, Mengdi Zhang, Zhi Li, Defu Lian, Enhong Chen

Sequential Recommendation is a widely studied paradigm for learning users' dynamic interests from historical interactions for predicting the next potential item.

Contrastive Learning Sequential Recommendation

Hierarchical Fuel-Cell Airpath Control: an Efficiency-Aware MIMO Control Approach Combined with a Novel Constraint-Enforcing Reference Governor

no code implementations25 Feb 2023 Eli Bacher-Chong, Mostafa Ali Ayubirad, Zeng Qiu, Hao Wang, Alireza Goshtasbi, Hamid R. Ossareh

Compared with a single-input single-output (SISO) air-flow control approach, the proposed MIMO control approach shows up to 7. 36 percent lower hydrogen fuel consumption.

AttentionMixer: An Accurate and Interpretable Framework for Process Monitoring

no code implementations21 Feb 2023 Hao Wang, Zhiyu Wang, Yunlong Niu, Zhaoran Liu, Haozhe Li, Yilin Liao, Yuxin Huang, Xinggao Liu

An accurate and explainable automatic monitoring system is critical for the safety of high efficiency energy conversion plants that operate under extreme working condition.

TMoE-P: Towards the Pareto Optimum for Multivariate Soft Sensors

no code implementations21 Feb 2023 Licheng Pan, Hao Wang, Zhichao Chen, Yuxing Huang, Xinggao Liu

We further present a Task-aware Mixture-of-Experts framework for achieving the Pareto optimum (TMoE-P) in multi-variate soft sensor, which consists of a stacked OMoE module and a POR module.

Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation

3 code implementations6 Feb 2023 Zihao Xu, Guang-Yuan Hao, Hao He, Hao Wang

To address this challenge, we first provide a formal definition of domain index from the probabilistic perspective, and then propose an adversarial variational Bayesian framework that infers domain indices from multi-domain data, thereby providing additional insight on domain relations and improving domain adaptation performance.

Domain Adaptation

Real-Time High-Resolution Pedestrian Detection in Crowded Scenes via Parallel Edge Offloading

no code implementations20 Jan 2023 Hao Wang, Hao Bao, Liekang Zeng, Ke Luo, Xu Chen

To identify dense and small-size pedestrians in surveillance systems, high-resolution cameras are widely deployed, where high-resolution images are captured and delivered to off-the-shelf pedestrian detection models.

Pedestrian Detection Scheduling

Fair Recommendation by Geometric Interpretation and Analysis of Matrix Factorization

no code implementations10 Jan 2023 Hao Wang

Matrix factorization-based recommender system is in effect an angle preserving dimensionality reduction technique.

Dimensionality Reduction Recommendation Systems

More is Better: A Database for Spontaneous Micro-Expression with High Frame Rates

no code implementations3 Jan 2023 Sirui Zhao, Huaying Tang, Xinglong Mao, Shifeng Liu, Hanqing Tao, Hao Wang, Tong Xu, Enhong Chen

To solve the problem of ME data hunger, we construct a dynamic spontaneous ME dataset with the largest current ME data scale, called DFME (Dynamic Facial Micro-expressions), which includes 7, 526 well-labeled ME videos induced by 671 participants and annotated by more than 20 annotators throughout three years.

Deep Reinforcement Learning for Wind and Energy Storage Coordination in Wholesale Energy and Ancillary Service Markets

no code implementations27 Dec 2022 Jinhao Li, Changlong Wang, Hao Wang

Simulations also show that using curtailed wind generation as a power source for charging the BESS can lead to additional financial gains.

energy trading Scheduling

First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting

1 code implementation15 Dec 2022 Xiyuan Zhang, Xiaoyong Jin, Karthick Gopalswamy, Gaurav Gupta, Youngsuk Park, Xingjian Shi, Hao Wang, Danielle C. Maddix, Yuyang Wang

Transformer-based models have gained large popularity and demonstrated promising results in long-term time-series forecasting in recent years.

Time Series Time Series Forecasting

Model-Free Approach to Fair Solar PV Curtailment Using Reinforcement Learning

no code implementations13 Dec 2022 Zhuo Wei, Frits de Nijs, Jinhao Li, Hao Wang

This paper investigates reinforcement learning, which gradually optimizes a fair PV curtailment strategy by interacting with the system.

Fairness reinforcement-learning +1

Proximal Policy Optimization Based Reinforcement Learning for Joint Bidding in Energy and Frequency Regulation Markets

no code implementations13 Dec 2022 Muhammad Anwar, Changlong Wang, Frits de Nijs, Hao Wang

Driven by the global decarbonization effort, the rapid integration of renewable energy into the conventional electricity grid presents new challenges and opportunities for the battery energy storage system (BESS) participating in the energy market.

Robust Perception through Equivariance

1 code implementation12 Dec 2022 Chengzhi Mao, Lingyu Zhang, Abhishek Joshi, Junfeng Yang, Hao Wang, Carl Vondrick

In this paper, we introduce a framework that uses the dense intrinsic constraints in natural images to robustify inference.

Adversarial Robustness Instance Segmentation +2

Complete cavity map of the C. elegans connectome

no code implementations7 Dec 2022 Bo Liu, Rongmei Yang, Hao Wang, Linyuan Lü

This study reports for the first time a complete cavity map of C. elegans neural network, developing a new method for mining higher-order structures that can be applied by researchers in neuroscience, network science and other interdisciplinary fields to explore higher-order structural markers of complex systems.

Pareto Pairwise Ranking for Fairness Enhancement of Recommender Systems

no code implementations6 Dec 2022 Hao Wang

Famous algorithms such as Bayesian Personalized Ranking and Collaborative Less is More Filtering have left deep impact in both academia and industry.

Fairness Learning-To-Rank +1

FedALA: Adaptive Local Aggregation for Personalized Federated Learning

2 code implementations2 Dec 2022 Jianqing Zhang, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan

A key challenge in federated learning (FL) is the statistical heterogeneity that impairs the generalization of the global model on each client.

Personalized Federated Learning

AL-iGAN: An Active Learning Framework for Tunnel Geological Reconstruction Based on TBM Operational Data

no code implementations2 Dec 2022 Hao Wang, Lixue Liu, Xueguan Song, Chao Zhang, DaCheng Tao

In tunnel boring machine (TBM) underground projects, an accurate description of the rock-soil types distributed in the tunnel can decrease the construction risk ({\it e. g.} surface settlement and landslide) and improve the efficiency of construction.

Active Learning Generative Adversarial Network

The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity

1 code implementation8 Nov 2022 André H. Deutz, Michael T. M. Emmerich, Hao Wang

Also, for the general $m$-dimensional case, a compact recursive analytical expression is established, and its algorithmic implementation is discussed.

Multiobjective Optimization Second-order methods

Fast Key Points Detection and Matching for Tree-Structured Images

no code implementations7 Nov 2022 Hao Wang, Xiwen Chen, Abolfazl Razi, Rahul Amin

The proposed algorithm is applicable to a variety of tree-structured image matching, but our focus is on dendrites, recently-developed visual identifiers.

Graph Matching Key Point Matching

R$^2$F: A General Retrieval, Reading and Fusion Framework for Document-level Natural Language Inference

1 code implementation22 Oct 2022 Hao Wang, Yixin Cao, Yangguang Li, Zhen Huang, Kun Wang, Jing Shao

Document-level natural language inference (DOCNLI) is a new challenging task in natural language processing, aiming at judging the entailment relationship between a pair of hypothesis and premise documents.

Natural Language Inference Retrieval +1

Entire Space Counterfactual Learning: Tuning, Analytical Properties and Industrial Applications

no code implementations20 Oct 2022 Hao Wang, Zhichao Chen, Jiajun Fan, Yuxin Huang, Weiming Liu, Xinggao Liu

As a basic research problem for building effective recommender systems, post-click conversion rate (CVR) estimation has long been plagued by sample selection bias and data sparsity issues.

Auxiliary Learning counterfactual +2

Federated Unlearning for On-Device Recommendation

no code implementations20 Oct 2022 Wei Yuan, Hongzhi Yin, Fangzhao Wu, Shijie Zhang, Tieke He, Hao Wang

It removes a user's contribution by rolling back and calibrating the historical parameter updates and then uses these updates to speed up federated recommender reconstruction.

Recommendation Systems

Visual Prompt Tuning for Test-time Domain Adaptation

no code implementations10 Oct 2022 Yunhe Gao, Xingjian Shi, Yi Zhu, Hao Wang, Zhiqiang Tang, Xiong Zhou, Mu Li, Dimitris N. Metaxas

First, DePT plugs visual prompts into the vision Transformer and only tunes these source-initialized prompts during adaptation.

Test-time Adaptation Unsupervised Domain Adaptation

1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct)

no code implementations7 Oct 2022 Hao Wang, WanYu Lin, Hao He, Di Wang, Chengzhi Mao, Muhan Zhang

Recent years have seen advances on principles and guidance relating to accountable and ethical use of artificial intelligence (AI) spring up around the globe.

ManiCLIP: Multi-Attribute Face Manipulation from Text

1 code implementation2 Oct 2022 Hao Wang, Guosheng Lin, Ana García del Molino, Anran Wang, Jiashi Feng, Zhiqi Shen

In this paper we present a novel multi-attribute face manipulation method based on textual descriptions.

Attribute Text-based Image Editing

Insurance Contract for High Renewable Energy Integration

no code implementations21 Sep 2022 Dongwei Zhao, Hao Wang, Jianwei Huang, Xiaojun Lin

A proper insurance design needs to resolve the following two challenges: (i) users' reliability preference is private information; and (ii) the insurance design is tightly coupled with the renewable energy investment decision.

Total Energy Vocal Bursts Intensity Prediction

Model Inversion Attacks against Graph Neural Networks

no code implementations16 Sep 2022 Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chee-Kong Lee, Enhong Chen

One famous privacy attack against data analysis models is the model inversion attack, which aims to infer sensitive data in the training dataset and leads to great privacy concerns.

Reinforcement Learning (RL)

LO-Det: Lightweight Oriented Object Detection in Remote Sensing Images

no code implementations16 Sep 2022 Zhanchao Huang, Wei Li, Xiang-Gen Xia, Hao Wang, Feiran Jie, Ran Tao

Specifically, a channel separation-aggregation (CSA) structure is designed to simplify the complexity of stacked separable convolutions, and a dynamic receptive field (DRF) mechanism is developed to maintain high accuracy by customizing the convolution kernel and its perception range dynamically when reducing the network complexity.

object-detection Object Detection +1

Multi-Grained Angle Representation for Remote Sensing Object Detection

1 code implementation7 Sep 2022 Hao Wang, Zhanchao Huang, Zhengchao Chen, Ying Song, Wei Li

The existing AOOD methods face the challenges of ambiguity and high costs in angle representation.

Object object-detection +2

Task-wise Sampling Convolutions for Arbitrary-Oriented Object Detection in Aerial Images

1 code implementation6 Sep 2022 Zhanchao Huang, Wei Li, Xiang-Gen Xia, Hao Wang, Ran Tao

However, the inconsistent features for the localization and classification tasks in AOOD models may lead to ambiguity and low-quality object predictions, which constrains the detection performance.

object-detection Object Detection In Aerial Images +1

Few-shot Incremental Event Detection

no code implementations5 Sep 2022 Hao Wang, Hanwen Shi, Jianyong Duan

In practice, however, the lack of high-quality labeled data of new event classes makes it difficult to obtain enough data for model training.

Event Detection Incremental Learning

Soft MIMO Detection Using Marginal Posterior Probability Statistics

no code implementations17 Aug 2022 Jiankun Zhang, Hao Wang, Jing Qian, Zhenxing Gao

Soft demodulation of received symbols into bit log-likelihood ratios (LLRs) is at the very heart of multiple-input-multiple-output (MIMO) detection.

Online Learning Based NLOS Ranging Error Mitigation in 5G Positioning

no code implementations16 Aug 2022 Jiankun Zhang, Hao Wang

The fifth-generation (5G) wireless communication is useful for positioning due to its large bandwidth and low cost.

Energy and Spectrum Efficient Federated Learning via High-Precision Over-the-Air Computation

no code implementations15 Aug 2022 Liang Li, Chenpei Huang, Dian Shi, Hao Wang, Xiangwei Zhou, Minglei Shu, Miao Pan

Guided by FL convergence analysis, we formulate a joint transmission probability and local computing control optimization, aiming to minimize the overall energy consumption (i. e., iterative local computing + multi-round communications) of mobile devices in FL.

Federated Learning

A Screening Strategy for Structured Optimization Involving Nonconvex $\ell_{q,p}$ Regularization

no code implementations2 Aug 2022 Tiange Li, Xiangyu Yang, Hao Wang

In this paper, we develop a simple yet effective screening rule strategy to improve the computational efficiency in solving structured optimization involving nonconvex $\ell_{q, p}$ regularization.

Computational Efficiency

3D Cartoon Face Generation with Controllable Expressions from a Single GAN Image

no code implementations29 Jul 2022 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

To this end, we discover the semantic meanings of StyleGAN latent space, such that we are able to produce face images of various expressions, poses, and lighting by controlling the latent codes.

Face Generation Face Model

Paired Cross-Modal Data Augmentation for Fine-Grained Image-to-Text Retrieval

no code implementations29 Jul 2022 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

When we do online paired data augmentation, we first generate augmented text through random token replacement, then pass the augmented text into the latent space alignment module to output the latent codes, which are finally fed to StyleGAN2 to generate the augmented images.

Cross-Modal Retrieval Data Augmentation +3

Subgraph Frequency Distribution Estimation using Graph Neural Networks

no code implementations14 Jul 2022 Zhongren Chen, Xinyue Xu, Shengyi Jiang, Hao Wang, Lu Mi

Small subgraphs (graphlets) are important features to describe fundamental units of a large network.

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting

1 code implementation12 Jul 2022 Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-yan Yeung

With the explosive growth of the spatiotemporal Earth observation data in the past decade, data-driven models that apply Deep Learning (DL) are demonstrating impressive potential for various Earth system forecasting tasks.

Earth Surface Forecasting Weather Forecasting

Enabling Harmonious Human-Machine Interaction with Visual-Context Augmented Dialogue System: A Review

no code implementations2 Jul 2022 Hao Wang, Bin Guo, Yating Zeng, Yasan Ding, Chen Qiu, Ying Zhang, Lina Yao, Zhiwen Yu

The intelligent dialogue system, aiming at communicating with humans harmoniously with natural language, is brilliant for promoting the advancement of human-machine interaction in the era of artificial intelligence.

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