| 2026 | ACL | RLSeek: Evidence-Grounded Reasoning for RAG Hallucination Detection. | Zhaoheng Huang, Dacheng Wen, Yutao Zhu, Xiaoying Lian, Yushi Liang, Kai Hao, Nan Li, Liangjie Zhang, Qi Zhang, Ji-Rong Wen, Zhicheng Dou, Fangzhao Wu |
| 2026 | ACL | SGT: Securing Open-Source LLMs Against Malicious Fine-tuning via Safety Guidance Trigger. | Sunguk Shin, Fangzhao Wu, Byung-Jun Lee, Meeyoung Cha, Sungwon Park |
| 2026 | ACL | Measuring Human Contribution in AI-Assisted Content Generation. | Yueqi Xie, Tao Qi, Jingwei Yi, Xiyuan Yang, Ryan Whalen, Junming Huang, Qian Ding, Yu Xie, Xing Xie, Fangzhao Wu |
| 2025 | EMNLP | Defending against Indirect Prompt Injection by Instruction Detection. | Tongyu Wen, Chenglong Wang, Xiyuan Yang, Haoyu Tang, Yueqi Xie, Lingjuan Lyu, Zhicheng Dou, Fangzhao Wu |
| 2025 | KDD | Benchmarking and Defending against Indirect Prompt Injection Attacks on Large Language Models. | Jingwei Yi, Yueqi Xie, Bin Zhu, Emre Kiciman, Guangzhong Sun, Xing Xie, Fangzhao Wu |
| 2024 | ACL | On the Vulnerability of Safety Alignment in Open-Access LLMs. | Jingwei Yi, Rui Ye, Qisi Chen, Bin Zhu, Siheng Chen, Defu Lian, Guangzhong Sun, Xing Xie, Fangzhao Wu |
| 2023 | ACL | Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark. | Wenjun Peng, Jingwei Yi, Fangzhao Wu, Shangxi Wu, Bin Zhu, Lingjuan Lyu, Binxing Jiao, Tong Xu, Guangzhong Sun, Xing Xie |
| 2023 | CIKM | Non-IID always Bad? Semi-Supervised Heterogeneous Federated Learning with Local Knowledge Enhancement. | Chao Zhang, Fangzhao Wu, Jingwei Yi, Derong Xu, Yang Yu, Jindong Wang, Yidong Wang, Tong Xu, Xing Xie, Enhong Chen |
| 2023 | ICCV | Towards Attack-tolerant Federated Learning via Critical Parameter Analysis. | Sungwon Han, Sungwon Park, Fangzhao Wu, Sundong Kim, Bin Zhu, Xing Xie, Meeyoung Cha |
| 2023 | ICML | Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting. | Yuchen Liu, Chen Chen, Lingjuan Lyu, Fangzhao Wu, Sai Wu, Gang Chen |
| 2023 | ICML | Personalized Federated Learning with Inferred Collaboration Graphs. | Rui Ye, Zhenyang Ni, Fangzhao Wu, Siheng Chen, Yanfeng Wang |
| 2023 | IJCAI | FedSampling: A Better Sampling Strategy for Federated Learning. | Tao Qi, Fangzhao Wu, Lingjuan Lyu, Yongfeng Huang, Xing Xie |
| 2023 | KDD | FedDefender: Client-Side Attack-Tolerant Federated Learning. | Sungwon Park, Sungwon Han, Fangzhao Wu, Sundong Kim, Bin Zhu, Xing Xie, Meeyoung Cha |
| 2023 | KDD | UA-FedRec: Untargeted Attack on Federated News Recommendation. | Jingwei Yi, Fangzhao Wu, Bin Zhu, Jing Yao, Zhulin Tao, Guangzhong Sun, Xing Xie |
| 2023 | RecSys | Rethinking Multi-Interest Learning for Candidate Matching in Recommender Systems. | Yueqi Xie, Jingqi Gao, Peilin Zhou, Qichen Ye, Yining Hua, Jae Boum Kim, Fangzhao Wu, Sunghun Kim |
| 2023 | WWW | DualFair: Fair Representation Learning at Both Group and Individual Levels via Contrastive Self-supervision. | Sungwon Han, SeungEon Lee, Fangzhao Wu, Sundong Kim, Chuhan Wu, Xiting Wang, Xing Xie, Meeyoung Cha |
| 2023 | WSDM | Federated Unlearning for On-Device Recommendation. | Wei Yuan, Hongzhi Yin, Fangzhao Wu, Shijie Zhang, Tieke He, Hao Wang |
| 2022 | AAAI | Protecting Intellectual Property of Language Generation APIs with Lexical Watermark. | Xuanli He, Qiongkai Xu, Lingjuan Lyu, Fangzhao Wu, Chenguang Wang |
| 2022 | ACL | NoisyTune: A Little Noise Can Help You Finetune Pretrained Language Models Better. | Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang |
| 2022 | ACL | Two Birds with One Stone: Unified Model Learning for Both Recall and Ranking in News Recommendation. | Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang |
| 2022 | ECCV | FedX: Unsupervised Federated Learning with Cross Knowledge Distillation. | Sungwon Han, Sungwon Park, Fangzhao Wu, Sundong Kim, Chuhan Wu, Xing Xie, Meeyoung Cha |
| 2022 | EMNLP | DebiasGAN: Eliminating Position Bias in News Recommendation with Adversarial Learning. | Chuhan Wu, Fangzhao Wu, Xiangnan He, Yongfeng Huang |
| 2022 | EMNLP | Effective and Efficient Query-aware Snippet Extraction for Web Search. | Jingwei Yi, Fangzhao Wu, Chuhan Wu, Xiaolong Huang, Binxing Jiao, Guangzhong Sun, Xing Xie |
| 2022 | EMNLP | Tiny-NewsRec: Effective and Efficient PLM-based News Recommendation. | Yang Yu, Fangzhao Wu, Chuhan Wu, Jingwei Yi, Qi Liu |
| 2022 | IJCAI | Rethinking InfoNCE: How Many Negative Samples Do You Need? | Chuhan Wu, Fangzhao Wu, Yongfeng Huang |
| 2022 | KDD | Personalized Chit-Chat Generation for Recommendation Using External Chat Corpora. | Changyu Chen, Xiting Wang, Xiaoyuan Yi, Fangzhao Wu, Xing Xie, Rui Yan |
| 2022 | KDD | No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices. | Ruixuan Liu, Fangzhao Wu, Chuhan Wu, Yanlin Wang, Lingjuan Lyu, Hong Chen, Xing Xie |
| 2022 | KDD | FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling. | Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang, Xing Xie |
| 2022 | KDD | Training Large-Scale News Recommenders with Pretrained Language Models in the Loop. | Shitao Xiao, Zheng Liu, Yingxia Shao, Tao Di, Bhuvan Middha, Fangzhao Wu, Xing Xie |
| 2022 | WWW | FeedRec: News Feed Recommendation with Various User Feedbacks. | Chuhan Wu, Fangzhao Wu, Tao Qi, Qi Liu, Xuan Tian, Jie Li, Wei He, Yongfeng Huang, Xing Xie |
| 2022 | SIGIR | News Recommendation with Candidate-aware User Modeling. | Tao Qi, Fangzhao Wu, Chuhan Wu, Yongfeng Huang |
| 2022 | SIGIR | FUM: Fine-grained and Fast User Modeling for News Recommendation. | Tao Qi, Fangzhao Wu, Chuhan Wu, Yongfeng Huang |
| 2022 | SIGIR | ProFairRec: Provider Fairness-aware News Recommendation. | Tao Qi, Fangzhao Wu, Chuhan Wu, Peijie Sun, Le Wu, Xiting Wang, Yongfeng Huang, Xing Xie |
| 2022 | SIGIR | UserBERT: Pre-training User Model with Contrastive Self-supervision. | Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang |
| 2022 | SIGIR | Is News Recommendation a Sequential Recommendation Task? | Chuhan Wu, Fangzhao Wu, Tao Qi, Chenliang Li, Yongfeng Huang |
| 2022 | SIGIR | MM-Rec: Visiolinguistic Model Empowered Multimodal News Recommendation. | Chuhan Wu, Fangzhao Wu, Tao Qi, Chao Zhang, Yongfeng Huang, Tong Xu |
| 2021 | AAAI | Fairness-aware News Recommendation with Decomposed Adversarial Learning. | Chuhan Wu, Fangzhao Wu, Xiting Wang, Yongfeng Huang, Xing Xie |
| 2021 | ACL | PP-Rec: News Recommendation with Personalized User Interest and Time-aware News Popularity. | Tao Qi, Fangzhao Wu, Chuhan Wu, Yongfeng Huang |
| 2021 | ACL | HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation. | Tao Qi, Fangzhao Wu, Chuhan Wu, Peiru Yang, Yang Yu, Xing Xie, Yongfeng Huang |
| 2021 | ACL | One Teacher is Enough? Pre-trained Language Model Distillation from Multiple Teachers. | Chuhan Wu, Fangzhao Wu, Yongfeng Huang |
| 2021 | ACL | Hi-Transformer: Hierarchical Interactive Transformer for Efficient and Effective Long Document Modeling. | Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang |
| 2021 | EMNLP | Uni-FedRec: A Unified Privacy-Preserving News Recommendation Framework for Model Training and Online Serving. | Tao Qi, Fangzhao Wu, Chuhan Wu, Yongfeng Huang, Xing Xie |
| 2021 | EMNLP | NewsBERT: Distilling Pre-trained Language Model for Intelligent News Application. | Chuhan Wu, Fangzhao Wu, Yang Yu, Tao Qi, Yongfeng Huang, Qi Liu |
| 2021 | EMNLP | Efficient-FedRec: Efficient Federated Learning Framework for Privacy-Preserving News Recommendation. | Jingwei Yi, Fangzhao Wu, Chuhan Wu, Ruixuan Liu, Guangzhong Sun, Xing Xie |
| 2021 | IJCAI | User-as-Graph: User Modeling with Heterogeneous Graph Pooling for News Recommendation. | Chuhan Wu, Fangzhao Wu, Yongfeng Huang, Xing Xie |
| 2021 | NAACL | DA-Transformer: Distance-aware Transformer. | Chuhan Wu, Fangzhao Wu, Yongfeng Huang |
| 2021 | SIGIR | Personalized News Recommendation with Knowledge-aware Interactive Matching. | Tao Qi, Fangzhao Wu, Chuhan Wu, Yongfeng Huang |
| 2021 | SIGIR | Joint Knowledge Pruning and Recurrent Graph Convolution for News Recommendation. | Yu Tian, Yuhao Yang, Xudong Ren, Pengfei Wang, Fangzhao Wu, Qian Wang, Chenliang Li |
| 2021 | SIGIR | Empowering News Recommendation with Pre-trained Language Models. | Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang |
| 2020 | ACL | Fine-grained Interest Matching for Neural News Recommendation. | Heyuan Wang, Fangzhao Wu, Zheng Liu, Xing Xie |
| 2020 | ACL | MIND: A Large-scale Dataset for News Recommendation. | Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, Chuhan Wu, Tao Qi, Jianxun Lian, Danyang Liu, Xing Xie, Jianfeng Gao, Winnie Wu, Ming Zhou |
| 2020 | ACL | Attentive Pooling with Learnable Norms for Text Representation. | Chuhan Wu, Fangzhao Wu, Tao Qi, Xiaohui Cui, Yongfeng Huang |
| 2020 | ECAI | A Multi-Task Learning Neural Network for Emotion-Cause Pair Extraction. | Sixing Wu, Fang Chen, Fangzhao Wu, Yongfeng Huang, Xing Li |
| 2020 | EMNLP | Privacy-Preserving News Recommendation Model Learning. | Tao Qi, Fangzhao Wu, Chuhan Wu, Yongfeng Huang, Xing Xie |
| 2020 | EMNLP | PTUM: Pre-training User Model from Unlabeled User Behaviors via Self-supervision. | Chuhan Wu, Fangzhao Wu, Tao Qi, Jianxun Lian, Yongfeng Huang, Xing Xie |
| 2020 | IJCAI | User Modeling with Click Preference and Reading Satisfaction for News Recommendation. | Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang |
| 2020 | IJCNLP | SentiRec: Sentiment Diversity-aware Neural News Recommendation. | Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang |
| 2020 | WWW | Graph Enhanced Representation Learning for News Recommendation. | Suyu Ge, Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang |
| 2019 | AAAI | DRr-Net: Dynamic Re-Read Network for Sentence Semantic Matching. | Kun Zhang, Guangyi Lv, Linyuan Wang, Le Wu, Enhong Chen, Fangzhao Wu, Xing Xie |
| 2019 | ACL | Neural News Recommendation with Long- and Short-term User Representations. | Mingxiao An, Fangzhao Wu, Chuhan Wu, Kun Zhang, Zheng Liu, Xing Xie |
| 2019 | ACL | Exploring Sequence-to-Sequence Learning in Aspect Term Extraction. | Dehong Ma, Sujian Li, Fangzhao Wu, Xing Xie, Houfeng Wang |
| 2019 | ACL | Neural News Recommendation with Topic-Aware News Representation. | Chuhan Wu, Fangzhao Wu, Mingxiao An, Yongfeng Huang, Xing Xie |
| 2019 | CIKM | NICE: Neural In-Hospital Cost Estimation from Medical Records. | Chuhan Wu, Fangzhao Wu, Yongfeng Huang, Xing Xie |
| 2019 | CIKM | Sentiment Lexicon Enhanced Neural Sentiment Classification. | Chuhan Wu, Fangzhao Wu, Junxin Liu, Yongfeng Huang, Xing Xie |
| 2019 | CIKM | ARP: Aspect-aware Neural Review Rating Prediction. | Chuhan Wu, Fangzhao Wu, Junxin Liu, Yongfeng Huang, Xing Xie |
| 2019 | CIKM | Neural Gender Prediction in Microblogging with Emotion-aware User Representation. | Chuhan Wu, Fangzhao Wu, Tao Qi, Junxin Liu, Yongfeng Huang, Xing Xie |
| 2019 | CIKM | Neural Review Rating Prediction with User and Product Memory. | Zhigang Yuan, Fangzhao Wu, Junxin Liu, Chuhan Wu, Yongfeng Huang, Xing Xie |
| 2019 | DASFAA | Neural Review Rating Prediction with Hierarchical Attentions and Latent Factors. | Xianchen Wang, Hongtao Liu, Peiyi Wang, Fangzhao Wu, Hongyan Xu, Wenjun Wang, Xing Xie |
| 2019 | EMNLP | Neural News Recommendation with Heterogeneous User Behavior. | Chuhan Wu, Fangzhao Wu, Mingxiao An, Tao Qi, Jianqiang Huang, Yongfeng Huang, Xing Xie |
| 2019 | EMNLP | Neural News Recommendation with Multi-Head Self-Attention. | Chuhan Wu, Fangzhao Wu, Suyu Ge, Tao Qi, Yongfeng Huang, Xing Xie |
| 2019 | EMNLP | Reviews Meet Graphs: Enhancing User and Item Representations for Recommendation with Hierarchical Attentive Graph Neural Network. | Chuhan Wu, Fangzhao Wu, Tao Qi, Suyu Ge, Yongfeng Huang, Xing Xie |
| 2019 | IJCAI | Hi-Fi Ark: Deep User Representation via High-Fidelity Archive Network. | Zheng Liu, Yu Xing, Fangzhao Wu, Mingxiao An, Xing Xie |
| 2019 | IJCAI | Neural News Recommendation with Attentive Multi-View Learning. | Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang, Xing Xie |
| 2019 | KDD | NPA: Neural News Recommendation with Personalized Attention. | Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang, Xing Xie |
| 2019 | NAACL | Hierarchical User and Item Representation with Three-Tier Attention for Recommendation. | Chuhan Wu, Fangzhao Wu, Junxin Liu, Yongfeng Huang |
| 2019 | WWW | Neural Chinese Word Segmentation with Lexicon and Unlabeled Data via Posterior Regularization. | Junxin Liu, Fangzhao Wu, Chuhan Wu, Yongfeng Huang, Xing Xie |
| 2019 | WWW | Neural Chinese Named Entity Recognition via CNN-LSTM-CRF and Joint Training with Word Segmentation. | Fangzhao Wu, Junxin Liu, Chuhan Wu, Yongfeng Huang, Xing Xie |
| 2019 | SIGIR | NRPA: Neural Recommendation with Personalized Attention. | Hongtao Liu, Fangzhao Wu, Wenjun Wang, Xianchen Wang, Pengfei Jiao, Chuhan Wu, Xing Xie |
| 2019 | WSDM | Neural Demographic Prediction using Search Query. | Chuhan Wu, Fangzhao Wu, Junxin Liu, Shaojian He, Yongfeng Huang, Xing Xie |
| 2019 | WSDM | MSA: Jointly Detecting Drug Name and Adverse Drug Reaction Mentioning Tweets with Multi-Head Self-Attention. | Chuhan Wu, Fangzhao Wu, Zhigang Yuan, Junxin Liu, Yongfeng Huang, Xing Xie |
| 2018 | CIKM | Imbalanced Sentiment Classification with Multi-Task Learning. | Fangzhao Wu, Chuhan Wu, Junxin Liu |
| 2018 | CIKM | Semi-Supervised Collaborative Learning for Social Spammer and Spam Message Detection in Microblogging. | Fangzhao Wu, Chuhan Wu, Junxin Liu |
| 2018 | ICDM | Neural Sentence-Level Sentiment Classification with Heterogeneous Supervision. | Zhigang Yuan, Fangzhao Wu, Junxin Liu, Chuhan Wu, Yongfeng Huang, Xing Xie |
| 2018 | ICDM | Image-Enhanced Multi-level Sentence Representation Net for Natural Language Inference. | Kun Zhang, Guangyi Lv, Le Wu, Enhong Chen, Qi Liu, Han Wu, Fangzhao Wu |
| 2017 | ACL | Active Sentiment Domain Adaptation. | Fangzhao Wu, Yongfeng Huang, Jun Yan |
| 2017 | IJCNLP | THU_NGN at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases with Deep LSTM. | Chuhan Wu, Fangzhao Wu, Yongfeng Huang, Sixing Wu, Zhigang Yuan |
| 2017 | SIGIR | Sentence-level Sentiment Classification with Weak Supervision. | Fangzhao Wu, Jia Zhang, Zhigang Yuan, Sixing Wu, Yongfeng Huang, Jun Yan |
| 2016 | AAAI | Personalized Microblog Sentiment Classification via Multi-Task Learning. | Fangzhao Wu, Yongfeng Huang |
| 2016 | ACL | Sentiment Domain Adaptation with Multiple Sources. | Fangzhao Wu, Yongfeng Huang |
| 2016 | CIKM | Sentiment Domain Adaptation with Multi-Level Contextual Sentiment Knowledge. | Fangzhao Wu, Sixing Wu, Yongfeng Huang, Songfang Huang, Yong Qin |
| 2015 | AAAI | Microblog Sentiment Classification with Contextual Knowledge Regularization. | Fangzhao Wu, Yangqiu Song, Yongfeng Huang |
| 2015 | CIKM | Social Spammer and Spam Message Co-Detection in Microblogging with Social Context Regularization. | Fangzhao Wu, Jinyun Shu, Yongfeng Huang, Zhigang Yuan |
| 2015 | ICDM | Collaborative Multi-domain Sentiment Classification. | Fangzhao Wu, Yongfeng Huang |
| 2014 | CIKM | Ranking Optimization with Constraints. | Fangzhao Wu, Jun Xu, Hang Li, Xin Jiang |
| 2013 | CIKM | Review rating prediction based on the content and weighting strong social relation of reviewers. | Bing-kun Wang, Yulin Min, Yongfeng Huang, Xing Li, Fangzhao Wu |
| 2013 | CIKM | Lead-lag analysis via sparse co-projection in correlated text streams. | Fangzhao Wu, Yangqiu Song, Shixia Liu, Yongfeng Huang, Zhenyu Liu |