default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDYongfeng Zhang 0003
Person information
- affiliation: Rutgers University, New Brunswick, NJ, USA
Other persons with the same name
- Yongfeng Zhang — disambiguation page
- Yongfeng Zhang 0001
![[0009-0001-5524-2053]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0009-0001-5524-2053")
— Shandong Normal University, Jinan, China - Yongfeng Zhang 0002 — China Education and Research Network, Beijing, China
- Yongfeng Zhang 0004 — Beihang University, Beijing, China
- Yongfeng Zhang 0005 — Rutgers University, New Brunswick, NJ, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
[j21]Shuyuan Xu, Jianchao Ji, Yunqi Li, Yingqiang Ge, Juntao Tan, Yongfeng Zhang:
Causal Inference for Recommendation: Foundations, Methods, and Applications. ACM Trans. Intell. Syst. Technol. 16(3): 51:1-51:51 (2025)- [j20]Guo Lin, Yongfeng Zhang:
Fuzzy Neural Logic Reasoning for Robust Classification. ACM Trans. Knowl. Discov. Data 19(2): 44:1-44:29 (2025) - [j19]Lina Yao, Julian J. McAuley, Yongfeng Zhang, Kun Zhang:
Introduction to the Special Issue on Causality Representation Learning in LLMs-Driven Recommender Systems. ACM Trans. Inf. Syst. 43(6): 142:1-142:3 (2025) - [j18]Yingqiang Ge, Shuchang Liu, Zuohui Fu, Juntao Tan, Zelong Li, Shuyuan Xu, Yunqi Li, Yikun Xian, Yongfeng Zhang:
A Survey on Trustworthy Recommender Systems. Trans. Recomm. Syst. 3(2): 13:1-13:68 (2025) - [c137]Mingyu Jin, Weidi Luo, Sitao Cheng, Xinyi Wang, Wenyue Hua, Ruixiang Tang, William Yang Wang, Yongfeng Zhang:
Disentangling Memory and Reasoning Ability in Large Language Models. ACL (1) 2025: 1681-1701 - [c136]Huaizhi Ge, Yiming Li, Qifan Wang, Yongfeng Zhang, Ruixiang Tang:
When Backdoors Speak: Understanding LLM Backdoor Attacks Through Model-Generated Explanations. ACL (1) 2025: 2278-2296 - [c135]Wenyue Hua, Kaijie Zhu, Lingyao Li, Lizhou Fan, Mingyu Jin, Shuhang Lin, Haochen Xue, Zelong Li, Jindong Wang, Yongfeng Zhang:
Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities. ACL (Findings) 2025: 19219-19242 - [c134]Mingyu Jin, Qinkai Yu, Jingyuan Huang, Qingcheng Zeng, Zhenting Wang, Wenyue Hua, Haiyan Zhao, Kai Mei, Yanda Meng, Kaize Ding, Fan Yang, Mengnan Du, Yongfeng Zhang:
Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers? COLING 2025: 558-573 - [c133]Zeru Shi, Kai Mei, Mingyu Jin, Yongye Su, Chaoji Zuo, Wenyue Hua, Wujiang Xu, Yujie Ren, Zirui Liu, Mengnan Du, Dong Deng, Yongfeng Zhang:
From Commands to Prompts: LLM-based Semantic File System for AIOS. ICLR 2025 - [c132]Guangyan Sun, Mingyu Jin, Zhenting Wang, Cheng-Long Wang, Siqi Ma, Qifan Wang, Tong Geng, Ying Nian Wu, Yongfeng Zhang, Dongfang Liu:
Visual Agents as Fast and Slow Thinkers. ICLR 2025 - [c131]Mansi Ranjit Mane, Djordje Gligorijevic, Dingxian Wang, Topojoy Biswas, Evren Körpeoglu, Marios Savvides, Yongfeng Zhang, Julian J. McAuley:
The Second Workshop on Generative AI for E-commerce. RecSys 2025: 1404-1408 - [c130]Qingsong Wen, Yongfeng Zhang, Zhiwei Liu, Julian J. McAuley, Hua Wei, Linsey Pang, Wei Liu, Philip S. Yu:
The 3rd Workshop on AI Agent for Information Retrieval: Generating and Ranking. WWW (Companion Volume) 2025: 1659-1662 - [i107]Mingyu Jin, Kai Mei, Wujiang Xu, Mingjie Sun, Ruixiang Tang, Mengnan Du, Zirui Liu, Yongfeng Zhang:
Massive Values in Self-Attention Modules are the Key to Contextual Knowledge Understanding. CoRR abs/2502.01563 (2025) - [i106]Zhaoqian Xue, Guanhong Liu, Kai Wei, Chong Zhang, Qingcheng Zeng, Songhua Hu, Wenyue Hua, Lizhou Fan, Yongfeng Zhang, Lingyao Li:
Toward Equitable Access: Leveraging Crowdsourced Reviews to Investigate Public Perceptions of Health Resource Accessibility. CoRR abs/2502.10641 (2025) - [i105]Xi Zhu, Haochen Xue, Ziwei Zhao, Wujiang Xu, Jingyuan Huang, Minghao Guo, Qifan Wang, Kaixiong Zhou, Yongfeng Zhang:
LLM as GNN: Graph Vocabulary Learning for Text-Attributed Graph Foundation Models. CoRR abs/2503.03313 (2025) - [i104]Junjie Xiong, Changjia Zhu, Shuhang Lin, Chong Zhang, Yongfeng Zhang, Yao Liu, Lingyao Li:
Invisible Prompts, Visible Threats: Malicious Font Injection in External Resources for Large Language Models. CoRR abs/2505.16957 (2025) - [i103]Bangde Du, Minghao Guo, Songming He, Ziyi Ye, Xi Zhu, Weihang Su, Shuqi Zhu, Yujia Zhou, Yongfeng Zhang, Qingyao Ai, Yiqun Liu:
TwinVoice: A Multi-dimensional Benchmark Towards Digital Twins via LLM Persona Simulation. CoRR abs/2510.25536 (2025) - [i102]Shuhang Lin, Zhencan Peng, Lingyao Li, Xiao Lin, Xi Zhu, Yongfeng Zhang:
Cache Mechanism for Agent RAG Systems. CoRR abs/2511.02919 (2025) - 2024
- [j17]Hua Tang, Chong Zhang, Mingyu Jin, Qinkai Yu, Zhenting Wang, Xiaobo Jin, Yongfeng Zhang, Mengnan Du:
Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities. SIGKDD Explor. 26(2): 109-118 (2024) - [j16]Zhichao Xu, Hansi Zeng, Juntao Tan, Zuohui Fu, Yongfeng Zhang, Qingyao Ai:
A Reusable Model-agnostic Framework for Faithfully Explainable Recommendation and System Scrutability. ACM Trans. Inf. Syst. 42(1): 29:1-29:29 (2024) - [j15]Yongfeng Zhang, Xu Chen, Da Xu, Tobias Schnabel:
Introduction to the Special Issue on Causal Inference for Recommender Systems. Trans. Recomm. Syst. 2(2): 1-4 (2024) - [c129]Mingyu Jin, Qinkai Yu, Dong Shu, Haiyan Zhao, Wenyue Hua, Yanda Meng, Yongfeng Zhang, Mengnan Du:
The Impact of Reasoning Step Length on Large Language Models. ACL (Findings) 2024: 1830-1842 - [c128]Dong Shu, Tianle Chen, Mingyu Jin, Chong Zhang, Mengnan Du, Yongfeng Zhang:
Knowledge Graph Large Language Model (KG-LLM) for Link Prediction. ACML 2024: 143-158 - [c127]Zelong Li, Yan Liang, Ming Wang, Sungro Yoon, Jiaying Shi, Xin Shen, Xiang He, Chenwei Zhang, Wenyi Wu, Hanbo Wang, Jin Li, Jim Chan, Yongfeng Zhang:
Explainable and Coherent Complement Recommendation Based on Large Language Models. CIKM 2024: 4678-4685 - [c126]Dong Shu, Haoran Zhao, Xukun Liu, David Demeter, Mengnan Du, Yongfeng Zhang:
LawLLM: Law Large Language Model for the US Legal System. CIKM 2024: 4882-4889 - [c125]Yunqi Li, Hanxiong Chen, Lanjing Zhang, Yongfeng Zhang:
Fairness in Survival Outcome Prediction for Medical Treatments. CISS 2024: 1-6 - [c124]Yunqi Li, Lanjing Zhang, Yongfeng Zhang:
Probing into the Fairness of Large Language Models: A Case Study of ChatGPT. CISS 2024: 1-6 - [c123]Lei Li, Yongfeng Zhang, Dugang Liu, Li Chen:
Large Language Models for Generative Recommendation: A Survey and Visionary Discussions. LREC/COLING 2024: 10146-10159 - [c122]Wenyue Hua, Yingqiang Ge, Shuyuan Xu, Jianchao Ji, Zelong Li, Yongfeng Zhang:
UP5: Unbiased Foundation Model for Fairness-aware Recommendation. EACL (1) 2024: 1899-1912 - [c121]Xinyi Li, Yongfeng Zhang, Edward C. Malthouse:
Large Language Model Agentic Approach to Fact Checking and Fake News Detection. ECAI 2024: 2572-2579 - [c120]Xinyi Li, Yongfeng Zhang, Edward C. Malthouse:
Prompt-Based Generative News Recommendation (PGNR): Accuracy and Controllability. ECIR (2) 2024: 66-79 - [c119]Jianchao Ji, Zelong Li, Shuyuan Xu, Wenyue Hua, Yingqiang Ge, Juntao Tan, Yongfeng Zhang:
GenRec: Large Language Model for Generative Recommendation. ECIR (3) 2024: 494-502 - [c118]Wenyue Hua, Xianjun Yang, Mingyu Jin, Zelong Li, Wei Cheng, Ruixiang Tang, Yongfeng Zhang:
TrustAgent: Towards Safe and Trustworthy LLM-based Agents. EMNLP (Findings) 2024: 10000-10016 - [c117]Juntao Tan, Shelby Heinecke, Zhiwei Liu, Yongjun Chen, Yongfeng Zhang, Huan Wang:
Towards More Robust and Accurate Sequential Recommendation with Cascade-guided Adversarial Training. SDM 2024: 743-751 - [c116]Runhui Wang, Luyang Kong, Yefan Tao, Andrew Borthwick, Davor Golac, Henrik Johnson, Shadie Hijazi, Dong Deng, Yongfeng Zhang:
Neural Locality Sensitive Hashing for Entity Blocking. SDM 2024: 887-895 - [c115]Juntao Tan, Shuyuan Xu, Wenyue Hua, Yingqiang Ge, Zelong Li, Yongfeng Zhang:
IDGenRec: LLM-RecSys Alignment with Textual ID Learning. SIGIR 2024: 355-364 - [c114]Shuyuan Xu, Wenyue Hua, Yongfeng Zhang:
OpenP5: An Open-Source Platform for Developing, Training, and Evaluating LLM-based Recommender Systems. SIGIR 2024: 386-394 - [i101]Mingyu Jin, Qinkai Yu, Dong Shu, Haiyan Zhao, Wenyue Hua, Yanda Meng, Yongfeng Zhang, Mengnan Du:
The Impact of Reasoning Step Length on Large Language Models. CoRR abs/2401.04925 (2024) - [i100]Dong Shu, Mingyu Jin, Suiyuan Zhu, Beichen Wang, Zihao Zhou, Chong Zhang, Yongfeng Zhang:
AttackEval: How to Evaluate the Effectiveness of Jailbreak Attacking on Large Language Models. CoRR abs/2401.09002 (2024) - [i99]Runhui Wang, Luyang Kong, Yefan Tao, Andrew Borthwick, Davor Golac, Henrik Johnson, Shadie Hijazi, Dong Deng, Yongfeng Zhang:
Neural Locality Sensitive Hashing for Entity Blocking. CoRR abs/2401.18064 (2024) - [i98]Zelong Li, Jianchao Ji, Yingqiang Ge, Wenyue Hua, Yongfeng Zhang:
PAP-REC: Personalized Automatic Prompt for Recommendation Language Model. CoRR abs/2402.00284 (2024) - [i97]Mingyu Jin, Qinkai Yu, Dong Shu, Chong Zhang, Lizhou Fan, Wenyue Hua, Suiyuan Zhu, Yanda Meng, Zhenting Wang, Mengnan Du, Yongfeng Zhang, Yanda Meng:
Health-LLM: Personalized Retrieval-Augmented Disease Prediction System. CoRR abs/2402.00746 (2024) - [i96]Zelong Li, Wenyue Hua, Hao Wang, He Zhu, Yongfeng Zhang:
Formal-LLM: Integrating Formal Language and Natural Language for Controllable LLM-based Agents. CoRR abs/2402.00798 (2024) - [i95]Wenyue Hua, Xianjun Yang, Zelong Li, Wei Cheng, Yongfeng Zhang:
TrustAgent: Towards Safe and Trustworthy LLM-based Agents through Agent Constitution. CoRR abs/2402.01586 (2024) - [i94]Mingyu Jin, Hua Tang, Chong Zhang, Qinkai Yu, Chengzhi Liu, Suiyuan Zhu, Yongfeng Zhang, Mengnan Du:
Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities. CoRR abs/2402.10835 (2024) - [i93]Lizhou Fan, Wenyue Hua, Xiang Li, Kaijie Zhu, Mingyu Jin, Lingyao Li, Haoyang Ling, Jinkui Chi, Jindong Wang, Xin Ma, Yongfeng Zhang:
NPHardEval4V: A Dynamic Reasoning Benchmark of Multimodal Large Language Models. CoRR abs/2403.01777 (2024) - [i92]Dong Shu, Tianle Chen, Mingyu Jin, Yiting Zhang, Chong Zhang, Mengnan Du, Yongfeng Zhang:
Knowledge Graph Large Language Model (KG-LLM) for Link Prediction. CoRR abs/2403.07311 (2024) - [i91]Kai Mei, Zelong Li, Shuyuan Xu, Ruosong Ye, Yingqiang Ge, Yongfeng Zhang:
AIOS: LLM Agent Operating System. CoRR abs/2403.16971 (2024) - [i90]Juntao Tan, Shuyuan Xu, Wenyue Hua, Yingqiang Ge, Zelong Li, Yongfeng Zhang:
Towards LLM-RecSys Alignment with Textual ID Learning. CoRR abs/2403.19021 (2024) - [i89]Mingyu Jin, Qinkai Yu, Jingyuan Huang, Qingcheng Zeng, Zhenting Wang, Wenyue Hua, Haiyan Zhao, Kai Mei, Yanda Meng, Kaize Ding, Fan Yang, Mengnan Du, Yongfeng Zhang:
Exploring Concept Depth: How Large Language Models Acquire Knowledge at Different Layers? CoRR abs/2404.07066 (2024) - [i88]Shuhang Lin, Wenyue Hua, Lingyao Li, Che-Jui Chang, Lizhou Fan, Jianchao Ji, Hang Hua, Mingyu Jin, Jiebo Luo, Yongfeng Zhang:
BattleAgent: Multi-modal Dynamic Emulation on Historical Battles to Complement Historical Analysis. CoRR abs/2404.15532 (2024) - [i87]Lingyao Li, Jiayan Zhou, Zhenxiang Gao, Wenyue Hua, Lizhou Fan, Huizi Yu, Loni Hagen, Yongfeng Zhang, Themistocles L. Assimes, Libby Hemphill, Siyuan Ma:
A scoping review of using Large Language Models (LLMs) to investigate Electronic Health Records (EHRs). CoRR abs/2405.03066 (2024) - [i86]Mingyu Jin, Haochen Xue, Zhenting Wang, Boming Kang, Ruosong Ye, Kaixiong Zhou, Mengnan Du, Yongfeng Zhang:
ProLLM: Protein Chain-of-Thoughts Enhanced LLM for Protein-Protein Interaction Prediction. CoRR abs/2405.06649 (2024) - [i85]Shuyuan Xu, Zelong Li, Kai Mei, Yongfeng Zhang:
AIOS Compiler: LLM as Interpreter for Natural Language Programming and Flow Programming of AI Agents. CoRR abs/2405.06907 (2024) - [i84]Wenyue Hua, Kaijie Zhu, Lingyao Li, Lizhou Fan, Shuhang Lin, Mingyu Jin, Haochen Xue, Zelong Li, Jindong Wang, Yongfeng Zhang:
Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities. CoRR abs/2406.02787 (2024) - [i83]Dong Shu, Mingyu Jin, Tianle Chen, Chong Zhang, Yongfeng Zhang:
Counterfactual Explainable Incremental Prompt Attack Analysis on Large Language Models. CoRR abs/2407.09292 (2024) - [i82]Qingcheng Zeng, Mingyu Jin, Qinkai Yu, Zhenting Wang, Wenyue Hua, Zihao Zhou, Guangyan Sun, Yanda Meng, Shiqing Ma, Qifan Wang, Felix Juefei-Xu, Kaize Ding, Fan Yang, Ruixiang Tang, Yongfeng Zhang:
Uncertainty is Fragile: Manipulating Uncertainty in Large Language Models. CoRR abs/2407.11282 (2024) - [i81]Zelong Li, Shuyuan Xu, Kai Mei, Wenyue Hua, Balaji Rama, Om Raheja, Hao Wang, He Zhu, Yongfeng Zhang:
AutoFlow: Automated Workflow Generation for Large Language Model Agents. CoRR abs/2407.12821 (2024) - [i80]Chong Zhang, Xinyi Liu, Mingyu Jin, Zhongmou Zhang, Lingyao Li, Zhenting Wang, Wenyue Hua, Dong Shu, Suiyuan Zhu, Xiaobo Jin, Sujian Li, Mengnan Du, Yongfeng Zhang:
When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments. CoRR abs/2407.18957 (2024) - [i79]Guangyan Sun, Mingyu Jin, Zhenting Wang, Cheng-Long Wang, Siqi Ma, Qifan Wang, Ying Nian Wu, Yongfeng Zhang, Dongfang Liu:
Visual Agents as Fast and Slow Thinkers. CoRR abs/2408.08862 (2024) - [i78]Zeru Shi, Kai Mei, Mingyu Jin, Yongye Su, Chaoji Zuo, Wenyue Hua, Wujiang Xu, Yujie Ren, Zirui Liu, Mengnan Du, Dong Deng, Yongfeng Zhang:
From Commands to Prompts: LLM-based Semantic File System for AIOS. CoRR abs/2410.11843 (2024) - [i77]Wenyue Hua, Ollie Liu, Lingyao Li, Alfonso Amayuelas, Julie Chen, Lucas Jiang, Mingyu Jin, Lizhou Fan, Fei Sun, William Wang, Xintong Wang, Yongfeng Zhang:
Game-theoretic LLM: Agent Workflow for Negotiation Games. CoRR abs/2411.05990 (2024) - [i76]Huaizhi Ge, Yiming Li, Qifan Wang, Yongfeng Zhang, Ruixiang Tang:
When Backdoors Speak: Understanding LLM Backdoor Attacks Through Model-Generated Explanations. CoRR abs/2411.12701 (2024) - [i75]Mingyu Jin, Weidi Luo, Sitao Cheng, Xinyi Wang, Wenyue Hua, Ruixiang Tang, William Yang Wang, Yongfeng Zhang:
Disentangling Memory and Reasoning Ability in Large Language Models. CoRR abs/2411.13504 (2024) - 2023
- [j14]Jianchao Ji, Zelong Li, Shuyuan Xu, Yingqiang Ge, Juntao Tan, Yongfeng Zhang:
Efficient Non-Sampling Graph Neural Networks. Inf. 14(8): 424 (2023) - [j13]Lei Li, Yongfeng Zhang, Li Chen:
On the Relationship between Explanation and Recommendation: Learning to Rank Explanations for Improved Performance. ACM Trans. Intell. Syst. Technol. 14(2): 21:1-21:24 (2023) - [j12]Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge, Juntao Tan, Shuchang Liu, Yongfeng Zhang:
Fairness in Recommendation: Foundations, Methods, and Applications. ACM Trans. Intell. Syst. Technol. 14(5): 95:1-95:48 (2023) - [j11]Xu Chen, Zhenlei Wang, Hongteng Xu, Jingsen Zhang, Yongfeng Zhang, Wayne Xin Zhao, Ji-Rong Wen:
Data Augmented Sequential Recommendation Based on Counterfactual Thinking. IEEE Trans. Knowl. Data Eng. 35(9): 9181-9194 (2023) - [j10]Lei Li, Yongfeng Zhang, Li Chen:
Personalized Prompt Learning for Explainable Recommendation. ACM Trans. Inf. Syst. 41(4): 103:1-103:26 (2023) - [j9]Shuyuan Xu, Juntao Tan, Shelby Heinecke, Vena Jia Li, Yongfeng Zhang:
Deconfounded Causal Collaborative Filtering. Trans. Recomm. Syst. 1(4): 1-25 (2023) - [c113]Lei Li, Yongfeng Zhang, Li Chen:
Prompt Distillation for Efficient LLM-based Recommendation. CIKM 2023: 1348-1357 - [c112]Juntao Tan, Yingqiang Ge, Yan Zhu, Yinglong Xia, Jiebo Luo, Jianchao Ji, Yongfeng Zhang:
User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations. ECAI 2023: 2307-2314 - [c111]Shijie Geng, Juntao Tan, Shuchang Liu, Zuohui Fu, Yongfeng Zhang:
VIP5: Towards Multimodal Foundation Models for Recommendation. EMNLP (Findings) 2023: 9606-9620 - [c110]Shuyuan Xu, Yingqiang Ge, Yunqi Li, Zuohui Fu, Xu Chen, Yongfeng Zhang:
Causal Collaborative Filtering. ICTIR 2023: 235-245 - [c109]Juntao Tan, Yongfeng Zhang:
ExplainableFold: Understanding AlphaFold Prediction with Explainable AI. KDD 2023: 2166-2176 - [c108]Yingqiang Ge, Wenyue Hua, Kai Mei, Jianchao Ji, Juntao Tan, Shuyuan Xu, Zelong Li, Yongfeng Zhang:
OpenAGI: When LLM Meets Domain Experts. NeurIPS 2023 - [c107]Wenyue Hua, Lei Li, Shuyuan Xu, Li Chen, Yongfeng Zhang:
Tutorial on Large Language Models for Recommendation. RecSys 2023: 1281-1283 - [c106]Wenyue Hua, Shuyuan Xu, Yingqiang Ge, Yongfeng Zhang:
How to Index Item IDs for Recommendation Foundation Models. SIGIR-AP 2023: 195-204 - [c105]Jianchao Ji, Zelong Li, Shuyuan Xu, Max Xiong, Juntao Tan, Yingqiang Ge, Hao Wang, Yongfeng Zhang:
Counterfactual Collaborative Reasoning. WSDM 2023: 249-257 - [c104]Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne R. Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu:
Tutorials at The Web Conference 2023. WWW (Companion Volume) 2023: 648-658 - [c103]Shuchang Liu, Qingpeng Cai, Bowen Sun, Yuhao Wang, Ji Jiang, Dong Zheng, Peng Jiang, Kun Gai, Xiangyu Zhao, Yongfeng Zhang:
Exploration and Regularization of the Latent Action Space in Recommendation. WWW 2023: 833-844 - [i74]Shuyuan Xu, Jianchao Ji, Yunqi Li, Yingqiang Ge, Juntao Tan, Yongfeng Zhang:
Causal Inference for Recommendation: Foundations, Methods and Applications. CoRR abs/2301.04016 (2023) - [i73]Shuchang Liu, Qingpeng Cai, Bowen Sun, Yuhao Wang, Ji Jiang, Dong Zheng, Kun Gai, Peng Jiang, Xiangyu Zhao, Yongfeng Zhang:
Exploration and Regularization of the Latent Action Space in Recommendation. CoRR abs/2302.03431 (2023) - [i72]Yingqiang Ge, Wenyue Hua, Kai Mei, Jianchao Ji, Juntao Tan, Shuyuan Xu, Zelong Li, Yongfeng Zhang:
OpenAGI: When LLM Meets Domain Experts. CoRR abs/2304.04370 (2023) - [i71]Juntao Tan, Shelby Heinecke, Zhiwei Liu, Yongjun Chen, Yongfeng Zhang, Huan Wang:
Towards More Robust and Accurate Sequential Recommendation with Cascade-guided Adversarial Training. CoRR abs/2304.05492 (2023) - [i70]Wenyue Hua, Shuyuan Xu, Yingqiang Ge, Yongfeng Zhang:
How to Index Item IDs for Recommendation Foundation Models. CoRR abs/2305.06569 (2023) - [i69]Wenyue Hua, Yingqiang Ge, Shuyuan Xu, Jianchao Ji, Yongfeng Zhang:
UP5: Unbiased Foundation Model for Fairness-aware Recommendation. CoRR abs/2305.12090 (2023) - [i68]Shijie Geng, Juntao Tan, Shuchang Liu, Zuohui Fu, Yongfeng Zhang:
VIP5: Towards Multimodal Foundation Models for Recommendation. CoRR abs/2305.14302 (2023) - [i67]Yunqi Li, Yongfeng Zhang:
Fairness of ChatGPT. CoRR abs/2305.18569 (2023) - [i66]Jianchao Ji, Zelong Li, Shuyuan Xu, Max Xiong, Juntao Tan, Yingqiang Ge, Hao Wang, Yongfeng Zhang:
Counterfactual Collaborative Reasoning. CoRR abs/2307.00165 (2023) - [i65]Jianchao Ji, Zelong Li, Shuyuan Xu, Wenyue Hua, Yingqiang Ge, Juntao Tan, Yongfeng Zhang:
GenRec: Large Language Model for Generative Recommendation. CoRR abs/2307.00457 (2023) - [i64]Juntao Tan, Yingqiang Ge, Yan Zhu, Yinglong Xia, Jiebo Luo, Jianchao Ji, Yongfeng Zhang:
User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations. CoRR abs/2308.00894 (2023) - [i63]Lei Li, Yongfeng Zhang, Dugang Liu, Li Chen:
Large Language Models for Generative Recommendation: A Survey and Visionary Discussions. CoRR abs/2309.01157 (2023) - [i62]Weixin Chen, Li Chen, Yongxin Ni, Yuhan Zhao, Fajie Yuan, Yongfeng Zhang:
FMMRec: Fairness-aware Multimodal Recommendation. CoRR abs/2310.17373 (2023) - [i61]Wenyue Hua, Lizhou Fan, Lingyao Li, Kai Mei, Jianchao Ji, Yingqiang Ge, Libby Hemphill, Yongfeng Zhang:
War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars. CoRR abs/2311.17227 (2023) - [i60]Yingqiang Ge, Yujie Ren, Wenyue Hua, Shuyuan Xu, Juntao Tan, Yongfeng Zhang:
LLM as OS, Agents as Apps: Envisioning AIOS, Agents and the AIOS-Agent Ecosystem. CoRR abs/2312.03815 (2023) - 2022
- [c102]Shijie Geng, Zuohui Fu, Yingqiang Ge, Lei Li, Gerard de Melo, Yongfeng Zhang:
Improving Personalized Explanation Generation through Visualization. ACL (1) 2022: 244-255 - [c101]Hanxiong Chen, Yunqi Li, He Zhu, Yongfeng Zhang:
Learn Basic Skills and Reuse: Modularized Adaptive Neural Architecture Search (MANAS). CIKM 2022: 169-179 - [c100]Shuyuan Xu, Juntao Tan, Zuohui Fu, Jianchao Ji, Shelby Heinecke, Yongfeng Zhang:
Dynamic Causal Collaborative Filtering. CIKM 2022: 2301-2310 - [c99]Yanbo Fang, Zuohui Fu, Xin Dong, Yongfeng Zhang, Gerard de Melo:
Assessing Combinational Generalization of Language Models in Biased Scenarios. AACL/IJCNLP (2) 2022: 392-397 - [c98]Yunqi Li, Hanxiong Chen, Juntao Tan, Yongfeng Zhang:
Causal factorization machine for robust recommendation. JCDL 2022: 10 - [c97]Shuchang Liu, Yingqiang Ge, Shuyuan Xu, Yongfeng Zhang, Amélie Marian:
Fairness-aware Federated Matrix Factorization. RecSys 2022: 168-178 - [c96]Shijie Geng, Shuchang Liu, Zuohui Fu, Yingqiang Ge, Yongfeng Zhang:
Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5). RecSys 2022: 299-315 - [c95]Yingqiang Ge, Juntao Tan, Yan Zhu, Yinglong Xia, Jiebo Luo, Shuchang Liu, Zuohui Fu, Shijie Geng, Zelong Li, Yongfeng Zhang:
Explainable Fairness in Recommendation. SIGIR 2022: 681-691 - [c94]Zelong Li, Jianchao Ji, Yingqiang Ge, Yongfeng Zhang:
AutoLossGen: Automatic Loss Function Generation for Recommender Systems. SIGIR 2022: 1304-1315 - [c93]Hanxiong Chen, Yunqi Li, Shaoyun Shi, Shuchang Liu, He Zhu, Yongfeng Zhang:
Graph Collaborative Reasoning. WSDM 2022: 75-84 - [c92]Yingqiang Ge, Xiaoting Zhao, Lucia Yu, Saurabh Paul, Diane Hu, Chu-Cheng Hsieh, Yongfeng Zhang:
Toward Pareto Efficient Fairness-Utility Trade-off in Recommendation through Reinforcement Learning. WSDM 2022: 316-324 - [c91]Zohreh Ovaisi, Shelby Heinecke, Jia Li, Yongfeng Zhang, Elena Zheleva, Caiming Xiong:
RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems. WSDM 2022: 1597-1600 - [c90]Shijie Geng, Zuohui Fu, Juntao Tan, Yingqiang Ge, Gerard de Melo, Yongfeng Zhang:
Path Language Modeling over Knowledge Graphsfor Explainable Recommendation. WWW 2022: 946-955 - [c89]Juntao Tan, Shijie Geng, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Yunqi Li, Yongfeng Zhang:
Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning. WWW 2022: 1018-1027 - [c88]Bingbing Wen, Yunhe Feng, Yongfeng Zhang, Chirag Shah:
ExpScore: Learning Metrics for Recommendation Explanation. WWW 2022: 3740-3744 - [i59]Yingqiang Ge, Xiaoting Zhao, Lucia Yu, Saurabh Paul, Diane Hu, Chu-Cheng Hsieh, Yongfeng Zhang:
Toward Pareto Efficient Fairness-Utility Trade-off inRecommendation through Reinforcement Learning. CoRR abs/2201.00140 (2022) - [i58]Zohreh Ovaisi, Shelby Heinecke, Jia Li, Yongfeng Zhang, Elena Zheleva, Caiming Xiong:
RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems. CoRR abs/2201.04399 (2022) - [i57]Xu Chen, Yongfeng Zhang, Ji-Rong Wen:
Measuring "Why" in Recommender Systems: a Comprehensive Survey on the Evaluation of Explainable Recommendation. CoRR abs/2202.06466 (2022) - [i56]Lei Li, Yongfeng Zhang, Li Chen:
Personalized Prompt Learning for Explainable Recommendation. CoRR abs/2202.07371 (2022) - [i55]Juntao Tan, Shijie Geng, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Yunqi Li, Yongfeng Zhang:
Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning. CoRR abs/2202.08816 (2022) - [i54]Shijie Geng, Shuchang Liu, Zuohui Fu, Yingqiang Ge, Yongfeng Zhang:
Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5). CoRR abs/2203.13366 (2022) - [i53]Yingqiang Ge, Juntao Tan, Yan Zhu, Yinglong Xia, Jiebo Luo, Shuchang Liu, Zuohui Fu, Shijie Geng, Zelong Li, Yongfeng Zhang:
Explainable Fairness in Recommendation. CoRR abs/2204.11159 (2022) - [i52]Zelong Li, Jianchao Ji, Yingqiang Ge, Yongfeng Zhang:
AutoLossGen: Automatic Loss Function Generation for Recommender Systems. CoRR abs/2204.13160 (2022) - [i51]Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge, Juntao Tan, Shuchang Liu, Yongfeng Zhang:
Fairness in Recommendation: A Survey. CoRR abs/2205.13619 (2022) - [i50]Yingqiang Ge, Shuchang Liu, Zuohui Fu, Juntao Tan, Zelong Li, Shuyuan Xu, Yunqi Li, Yikun Xian, Yongfeng Zhang:
A Survey on Trustworthy Recommender Systems. CoRR abs/2207.12515 (2022) - [i49]Bingbing Wen, Yunhe Feng, Yongfeng Zhang, Chirag Shah:
Towards Generating Robust, Fair, and Emotion-Aware Explanations for Recommender Systems. CoRR abs/2208.08017 (2022) - [i48]Hanxiong Chen, Yunqi Li, He Zhu, Yongfeng Zhang:
Learn Basic Skills and Reuse: Modularized Adaptive Neural Architecture Search (MANAS). CoRR abs/2208.11083 (2022) - [i47]Shuyuan Xu, Juntao Tan, Zuohui Fu, Jianchao Ji, Shelby Heinecke, Yongfeng Zhang:
Dynamic Causal Collaborative Filtering. CoRR abs/2208.11094 (2022) - 2021
- [c87]Lei Li, Yongfeng Zhang, Li Chen:
Personalized Transformer for Explainable Recommendation. ACL/IJCNLP (1) 2021: 4947-4957 - [c86]Zuohui Fu, Yikun Xian, Shijie Geng, Gerard de Melo, Yongfeng Zhang:
Popcorn: Human-in-the-loop Popularity Debiasing in Conversational Recommender Systems. CIKM 2021: 494-503 - [c85]Juntao Tan, Shuyuan Xu, Yingqiang Ge, Yunqi Li, Xu Chen, Yongfeng Zhang:
Counterfactual Explainable Recommendation. CIKM 2021: 1784-1793 - [c84]Kun Xiong, Wenwen Ye, Xu Chen, Yongfeng Zhang, Wayne Xin Zhao, Binbin Hu, Zhiqiang Zhang, Jun Zhou:
Counterfactual Review-based Recommendation. CIKM 2021: 2231-2240 - [c83]Yunqi Li, Yingqiang Ge, Yongfeng Zhang:
CIKM 2021 Tutorial on Fairness of Machine Learning in Recommender Systems. CIKM 2021: 4857-4860 - [c82]Zuohui Fu, Yikun Xian, Yongfeng Zhang, Yi Zhang:
IUI 2021 Tutorial on Conversational Recommendation Systems. IUI Companion 2021: 1-2 - [c81]Yaxin Zhu, Yikun Xian, Zuohui Fu, Gerard de Melo, Yongfeng Zhang:
Faithfully Explainable Recommendation via Neural Logic Reasoning. NAACL-HLT 2021: 3083-3090 - [c80]Yikun Xian, Tong Zhao, Jin Li, Jim Chan, Andrey Kan, Jun Ma, Xin Luna Dong, Christos Faloutsos, George Karypis, S. Muthukrishnan, Yongfeng Zhang:
EX3: Explainable Attribute-aware Item-set Recommendations. RecSys 2021: 484-494 - [c79]Zhenlei Wang, Jingsen Zhang, Hongteng Xu, Xu Chen, Yongfeng Zhang, Wayne Xin Zhao, Ji-Rong Wen:
Counterfactual Data-Augmented Sequential Recommendation. SIGIR 2021: 347-356 - [c78]Shuchang Liu, Shuyuan Xu, Wenhui Yu, Zuohui Fu, Yongfeng Zhang, Amélie Marian:
FedCT: Federated Collaborative Transfer for Recommendation. SIGIR 2021: 716-725 - [c77]Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge, Yongfeng Zhang:
Towards Personalized Fairness based on Causal Notion. SIGIR 2021: 1054-1063 - [c76]Zuohui Fu, Yikun Xian, Yaxin Zhu, Shuyuan Xu, Zelong Li, Gerard de Melo, Yongfeng Zhang:
HOOPS: Human-in-the-Loop Graph Reasoning for Conversational Recommendation. SIGIR 2021: 2415-2421 - [c75]Lei Li, Yongfeng Zhang, Li Chen:
EXTRA: Explanation Ranking Datasets for Explainable Recommendation. SIGIR 2021: 2463-2469 - [c74]Yunqi Li, Yingqiang Ge, Yongfeng Zhang:
Tutorial on Fairness of Machine Learning in Recommender Systems. SIGIR 2021: 2654-2657 - [c73]Yongfeng Zhang, Xu Chen, Yi Zhang, Xianjie Chen:
CSR 2021: The 1st International Workshop on Causality in Search and Recommendation. SIGIR 2021: 2677-2680 - [c72]Yingqiang Ge, Shuchang Liu, Ruoyuan Gao, Yikun Xian, Yunqi Li, Xiangyu Zhao, Changhua Pei, Fei Sun, Junfeng Ge, Wenwu Ou, Yongfeng Zhang:
Towards Long-term Fairness in Recommendation. WSDM 2021: 445-453 - [c71]Zuohui Fu, Yikun Xian, Yongfeng Zhang, Yi Zhang:
WSDM 2021 Tutorial on Conversational Recommendation Systems. WSDM 2021: 1134-1136 - [c70]Yongfeng Zhang, Min Zhang, Hanxiong Chen, Xu Chen, Xianjie Chen, Chuang Gan, Tong Sun, Xin Luna Dong:
The 1st International Workshop on Machine Reasoning: International Machine Reasoning Conference (MRC 2021). WSDM 2021: 1161-1162 - [c69]Shuchang Liu, Fei Sun, Yingqiang Ge, Changhua Pei, Yongfeng Zhang:
Variation Control and Evaluation for Generative Slate Recommendations. WWW 2021: 436-448 - [c68]Yunqi Li, Hanxiong Chen, Zuohui Fu, Yingqiang Ge, Yongfeng Zhang:
User-oriented Fairness in Recommendation. WWW 2021: 624-632 - [c67]Hanxiong Chen, Shaoyun Shi, Yunqi Li, Yongfeng Zhang:
Neural Collaborative Reasoning. WWW 2021: 1516-1527 - [c66]Zelong Li, Jianchao Ji, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Chong Chen, Yongfeng Zhang:
Efficient Non-Sampling Knowledge Graph Embedding. WWW 2021: 1727-1736 - [i46]Hanxiong Chen, Xu Chen, Shaoyun Shi, Yongfeng Zhang:
Generate Natural Language Explanations for Recommendation. CoRR abs/2101.03392 (2021) - [i45]Yingqiang Ge, Shuchang Liu, Ruoyuan Gao, Yikun Xian, Yunqi Li, Xiangyu Zhao, Changhua Pei, Fei Sun, Junfeng Ge, Wenwu Ou, Yongfeng Zhang:
Towards Long-term Fairness in Recommendation. CoRR abs/2101.03584 (2021) - [i44]Yunqi Li, Shuyuan Xu, Bo Liu, Zuohui Fu, Shuchang Liu, Xu Chen, Yongfeng Zhang:
Discrete Knowledge Graph Embedding based on Discrete Optimization. CoRR abs/2101.04817 (2021) - [i43]Lei Li, Yongfeng Zhang, Li Chen:
Learning to Explain Recommendations. CoRR abs/2102.00627 (2021) - [i42]Shuyuan Xu, Yingqiang Ge, Yunqi Li, Zuohui Fu, Xu Chen, Yongfeng Zhang:
Causal Collaborative Filtering. CoRR abs/2102.01868 (2021) - [i41]Lei Li, Yongfeng Zhang, Li Chen:
EXTRA: Explanation Ranking Datasets for Explainable Recommendation. CoRR abs/2102.10315 (2021) - [i40]Shuchang Liu, Fei Sun, Yingqiang Ge, Changhua Pei, Yongfeng Zhang:
Variation Control and Evaluation for Generative SlateRecommendations. CoRR abs/2102.13302 (2021) - [i39]Yaxin Zhu, Yikun Xian, Zuohui Fu, Gerard de Melo, Yongfeng Zhang:
Faithfully Explainable Recommendation via Neural Logic Reasoning. CoRR abs/2104.07869 (2021) - [i38]Yunqi Li, Hanxiong Chen, Zuohui Fu, Yingqiang Ge, Yongfeng Zhang:
User-oriented Fairness in Recommendation. CoRR abs/2104.10671 (2021) - [i37]Zelong Li, Jianchao Ji, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Chong Chen, Yongfeng Zhang:
Efficient Non-Sampling Knowledge Graph Embedding. CoRR abs/2104.10796 (2021) - [i36]Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge, Yongfeng Zhang:
Towards Personalized Fairness based on Causal Notion. CoRR abs/2105.09829 (2021) - [i35]Lei Li, Yongfeng Zhang, Li Chen:
Personalized Transformer for Explainable Recommendation. CoRR abs/2105.11601 (2021) - [i34]Juntao Tan, Shuyuan Xu, Yingqiang Ge, Yunqi Li, Xu Chen, Yongfeng Zhang:
Counterfactual Explainable Recommendation. CoRR abs/2108.10539 (2021) - [i33]Yingqiang Ge, Shuchang Liu, Zelong Li, Shuyuan Xu, Shijie Geng, Yunqi Li, Juntao Tan, Fei Sun, Yongfeng Zhang:
Counterfactual Evaluation for Explainable AI. CoRR abs/2109.01962 (2021) - [i32]Shuyuan Xu, Juntao Tan, Shelby Heinecke, Jia Li, Yongfeng Zhang:
Deconfounded Causal Collaborative Filtering. CoRR abs/2110.07122 (2021) - [i31]Zelong Li, Jianchao Ji, Yongfeng Zhang:
From Kepler to Newton: Explainable AI for Science Discovery. CoRR abs/2111.12210 (2021) - [i30]Hanxiong Chen, Yunqi Li, Shaoyun Shi, Shuchang Liu, He Zhu, Yongfeng Zhang:
Graph Collaborative Reasoning. CoRR abs/2112.13705 (2021) - 2020
- [j8]Yongfeng Zhang, Xu Chen:
Explainable Recommendation: A Survey and New Perspectives. Found. Trends Inf. Retr. 14(1): 1-101 (2020) - [j7]Qingyao Ai, Yongfeng Zhang, Keping Bi, W. Bruce Croft:
Explainable Product Search with a Dynamic Relation Embedding Model. ACM Trans. Inf. Syst. 38(1): 4:1-4:29 (2020) - [j6]Chong Chen, Min Zhang, Yongfeng Zhang, Yiqun Liu, Shaoping Ma:
Efficient Neural Matrix Factorization without Sampling for Recommendation. ACM Trans. Inf. Syst. 38(2): 14:1-14:28 (2020) - [j5]Xu Chen, Kun Xiong, Yongfeng Zhang, Long Xia, Dawei Yin, Jimmy Xiangji Huang:
Neural Feature-aware Recommendation with Signed Hypergraph Convolutional Network. ACM Trans. Inf. Syst. 39(1): 8:1-8:22 (2020) - [c65]Chong Chen, Min Zhang, Yongfeng Zhang, Weizhi Ma, Yiqun Liu, Shaoping Ma:
Efficient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation. AAAI 2020: 19-26 - [c64]Lei Li, Yongfeng Zhang, Li Chen:
Generate Neural Template Explanations for Recommendation. CIKM 2020: 755-764 - [c63]Shaoyun Shi, Hanxiong Chen, Weizhi Ma, Jiaxin Mao, Min Zhang, Yongfeng Zhang:
Neural Logic Reasoning. CIKM 2020: 1365-1374 - [c62]Yikun Xian, Zuohui Fu, Handong Zhao, Yingqiang Ge, Xu Chen, Qiaoying Huang, Shijie Geng, Zhou Qin, Gerard de Melo, S. Muthukrishnan, Yongfeng Zhang:
CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation. CIKM 2020: 1645-1654 - [c61]Zhichao Xu, Yi Han, Yongfeng Zhang, Qingyao Ai:
E-commerce Recommendation with Weighted Expected Utility. CIKM 2020: 1695-1704 - [c60]Honglu Zhou, Shuyuan Xu, Zuohui Fu, Gerard de Melo, Yongfeng Zhang, Mubbasir Kapadia:
HID: Hierarchical Multiscale Representation Learning for Information Diffusion. IJCAI 2020: 3385-3391 - [c59]Zuohui Fu, Yikun Xian, Yongfeng Zhang, Yi Zhang:
Tutorial on Conversational Recommendation Systems. RecSys 2020: 751-753 - [c58]Zuohui Fu, Yikun Xian, Ruoyuan Gao, Jieyu Zhao, Qiaoying Huang, Yingqiang Ge, Shuyuan Xu, Shijie Geng, Chirag Shah, Yongfeng Zhang, Gerard de Melo:
Fairness-Aware Explainable Recommendation over Knowledge Graphs. SIGIR 2020: 69-78 - [c57]Shaoyun Shi, Weizhi Ma, Min Zhang, Yongfeng Zhang, Xinxing Yu, Houzhi Shan, Yiqun Liu, Shaoping Ma:
Beyond User Embedding Matrix: Learning to Hash for Modeling Large-Scale Users in Recommendation. SIGIR 2020: 319-328 - [c56]Yingqiang Ge, Shuyuan Xu, Shuchang Liu, Zuohui Fu, Fei Sun, Yongfeng Zhang:
Learning Personalized Risk Preferences for Recommendation. SIGIR 2020: 409-418 - [c55]Yingqiang Ge, Shuya Zhao, Honglu Zhou, Changhua Pei, Fei Sun, Wenwu Ou, Yongfeng Zhang:
Understanding Echo Chambers in E-commerce Recommender Systems. SIGIR 2020: 2261-2270 - [c54]Yongfeng Zhang, Xu Chen, Yi Zhang, Min Zhang, Chirag Shah:
EARS 2020: The 3rd International Workshop on ExplainAble Recommendation and Search. SIGIR 2020: 2472-2474 - [c53]Lei Li, Li Chen, Yongfeng Zhang:
Towards Controllable Explanation Generation for Recommender Systems via Neural Template. WWW (Companion Volume) 2020: 198-202 - [c52]Liu Yang, Minghui Qiu, Chen Qu, Cen Chen, Jiafeng Guo, Yongfeng Zhang, W. Bruce Croft, Haiqing Chen:
IART: Intent-aware Response Ranking with Transformers in Information-seeking Conversation Systems. WWW 2020: 2592-2598 - [i29]Liu Yang, Minghui Qiu, Chen Qu, Cen Chen, Jiafeng Guo, Yongfeng Zhang, W. Bruce Croft, Haiqing Chen:
IART: Intent-aware Response Ranking with Transformers in Information-seeking Conversation Systems. CoRR abs/2002.00571 (2020) - [i28]Hanxiong Chen, Shaoyun Shi, Yunqi Li, Yongfeng Zhang:
Neural Collaborative Reasoning. CoRR abs/2005.08129 (2020) - [i27]Zuohui Fu, Yikun Xian, Ruoyuan Gao, Jieyu Zhao, Qiaoying Huang, Yingqiang Ge, Shuyuan Xu, Shijie Geng, Chirag Shah, Yongfeng Zhang, Gerard de Melo:
Fairness-Aware Explainable Recommendation over Knowledge Graphs. CoRR abs/2006.02046 (2020) - [i26]Shuyuan Xu, Yunqi Li, Shuchang Liu, Zuohui Fu, Yongfeng Zhang:
Learning Post-Hoc Causal Explanations for Recommendation. CoRR abs/2006.16977 (2020) - [i25]Yingqiang Ge, Shuya Zhao, Honglu Zhou, Changhua Pei, Fei Sun, Wenwu Ou, Yongfeng Zhang:
Understanding Echo Chambers in E-commerce Recommender Systems. CoRR abs/2007.02474 (2020) - [i24]Yingqiang Ge, Shuyuan Xu, Shuchang Liu, Zuohui Fu, Fei Sun, Yongfeng Zhang:
Learning Personalized Risk Preferences for Recommendation. CoRR abs/2007.02478 (2020) - [i23]Yikun Xian, Zuohui Fu, Qiaoying Huang, S. Muthukrishnan, Yongfeng Zhang:
Neural-Symbolic Reasoning over Knowledge Graph for Multi-stage Explainable Recommendation. CoRR abs/2007.13207 (2020) - [i22]Zhichao Xu, Yi Han, Yongfeng Zhang, Qingyao Ai:
E-commerce Recommendation with Weighted Expected Utility. CoRR abs/2008.08302 (2020) - [i21]Zuohui Fu, Yikun Xian, Yaxin Zhu, Yongfeng Zhang, Gerard de Melo:
COOKIE: A Dataset for Conversational Recommendation over Knowledge Graphs in E-commerce. CoRR abs/2008.09237 (2020) - [i20]Shaoyun Shi, Hanxiong Chen, Weizhi Ma, Jiaxin Mao, Min Zhang, Yongfeng Zhang:
Neural Logic Reasoning. CoRR abs/2008.09514 (2020) - [i19]Yikun Xian, Zuohui Fu, Handong Zhao, Yingqiang Ge, Xu Chen, Qiaoying Huang, Shijie Geng, Zhou Qin, Gerard de Melo, S. Muthukrishnan, Yongfeng Zhang:
CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation. CoRR abs/2010.15620 (2020)
2010 – 2019
- 2019
- [j4]Pengfei Wang, Yongfeng Zhang, Shuzi Niu, Jiafeng Guo:
Modeling Temporal Dynamics of Users' Purchase Behaviors for Next Basket Prediction. J. Comput. Sci. Technol. 34(6): 1230-1240 (2019) - [j3]Xu Chen, Yongfeng Zhang, Hongteng Xu, Zheng Qin, Hongyuan Zha:
Adversarial Distillation for Efficient Recommendation with External Knowledge. ACM Trans. Inf. Syst. 37(1): 12:1-12:28 (2019) - [c51]Xu Chen, Yongfeng Zhang, Zheng Qin:
Dynamic Explainable Recommendation Based on Neural Attentive Models. AAAI 2019: 53-60 - [c50]Chen Qu, Liu Yang, W. Bruce Croft, Yongfeng Zhang, Johanne R. Trippas, Minghui Qiu:
User Intent Prediction in Information-seeking Conversations. CHIIR 2019: 25-33 - [c49]Chen Qu, Liu Yang, W. Bruce Croft, Falk Scholer, Yongfeng Zhang:
Answer Interaction in Non-factoid Question Answering Systems. CHIIR 2019: 249-253 - [c48]Keping Bi, Qingyao Ai, Yongfeng Zhang, W. Bruce Croft:
Conversational Product Search Based on Negative Feedback. CIKM 2019: 359-368 - [c47]Chen Qu, Liu Yang, Minghui Qiu, Yongfeng Zhang, Cen Chen, W. Bruce Croft, Mohit Iyyer:
Attentive History Selection for Conversational Question Answering. CIKM 2019: 1391-1400 - [c46]Shaoyun Shi, Min Zhang, Xinxing Yu, Yongfeng Zhang, Bin Hao, Yiqun Liu, Shaoping Ma:
Adaptive Feature Sampling for Recommendation with Missing Content Feature Values. CIKM 2019: 1451-1460 - [c45]Changhua Pei, Yi Zhang, Yongfeng Zhang, Fei Sun, Xiao Lin, Hanxiao Sun, Jian Wu, Peng Jiang, Junfeng Ge, Wenwu Ou, Dan Pei:
Personalized re-ranking for recommendation. RecSys 2019: 3-11 - [c44]Xiao Lin, Hongjie Chen, Changhua Pei, Fei Sun, Xuanji Xiao, Hanxiao Sun, Yongfeng Zhang, Wenwu Ou, Peng Jiang:
A pareto-efficient algorithm for multiple objective optimization in e-commerce recommendation. RecSys 2019: 20-28 - [c43]Pengfei Wang, Hanxiong Chen, Yadong Zhu, Huawei Shen, Yongfeng Zhang:
Unified Collaborative Filtering over Graph Embeddings. SIGIR 2019: 155-164 - [c42]Yikun Xian, Zuohui Fu, S. Muthukrishnan, Gerard de Melo, Yongfeng Zhang:
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation. SIGIR 2019: 285-294 - [c41]Pengfei Wang, Yu Fan, Shuzi Niu, Ze Yang, Yongfeng Zhang, Jiafeng Guo:
Hierarchical Matching Network for Crime Classification. SIGIR 2019: 325-334 - [c40]Xu Chen, Hanxiong Chen, Hongteng Xu, Yongfeng Zhang, Yixin Cao, Zheng Qin, Hongyuan Zha:
Personalized Fashion Recommendation with Visual Explanations based on Multimodal Attention Network: Towards Visually Explainable Recommendation. SIGIR 2019: 765-774 - [c39]Chen Qu, Liu Yang, Minghui Qiu, W. Bruce Croft, Yongfeng Zhang, Mohit Iyyer:
BERT with History Answer Embedding for Conversational Question Answering. SIGIR 2019: 1133-1136 - [c38]Yongfeng Zhang, Jiaxin Mao, Qingyao Ai:
SIGIR 2019 Tutorial on Explainable Recommendation and Search. SIGIR 2019: 1417-1418 - [c37]Yongfeng Zhang, Yi Zhang, Min Zhang, Chirag Shah:
EARS 2019: The 2nd International Workshop on ExplainAble Recommendation and Search. SIGIR 2019: 1438-1440 - [c36]Yongfeng Zhang, Jiaxin Mao, Qingyao Ai:
WWW'19 Tutorial on Explainable Recommendation and Search. WWW (Companion Volume) 2019: 1330-1331 - [c35]Yingqiang Ge, Shuyuan Xu, Shuchang Liu, Shijie Geng, Zuohui Fu, Yongfeng Zhang:
Maximizing Marginal Utility per Dollar for Economic Recommendation. WWW 2019: 2757-2763 - [c34]Changhua Pei, Xinru Yang, Qing Cui, Xiao Lin, Fei Sun, Peng Jiang, Wenwu Ou, Yongfeng Zhang:
Value-aware Recommendation based on Reinforcement Profit Maximization. WWW 2019: 3123-3129 - [i18]Chen Qu, Liu Yang, W. Bruce Croft, Yongfeng Zhang, Johanne R. Trippas, Minghui Qiu:
User Intent Prediction in Information-seeking Conversations. CoRR abs/1901.03489 (2019) - [i17]Chen Qu, Liu Yang, W. Bruce Croft, Falk Scholer, Yongfeng Zhang:
Answer Interaction in Non-factoid Question Answering Systems. CoRR abs/1901.03491 (2019) - [i16]Changhua Pei, Xinru Yang, Qing Cui, Xiao Lin, Fei Sun, Peng Jiang, Wenwu Ou, Yongfeng Zhang:
Value-aware Recommendation based on Reinforced Profit Maximization in E-commerce Systems. CoRR abs/1902.00851 (2019) - [i15]Changhua Pei, Yi Zhang, Yongfeng Zhang, Fei Sun, Xiao Lin, Hanxiao Sun, Jian Wu, Peng Jiang, Wenwu Ou, Dan Pei:
Personalized Context-aware Re-ranking for E-commerce Recommender Systems. CoRR abs/1904.06813 (2019) - [i14]Chen Qu, Liu Yang, Minghui Qiu, W. Bruce Croft, Yongfeng Zhang, Mohit Iyyer:
BERT with History Answer Embedding for Conversational Question Answering. CoRR abs/1905.05412 (2019) - [i13]Yikun Xian, Zuohui Fu, S. Muthukrishnan, Gerard de Melo, Yongfeng Zhang:
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation. CoRR abs/1906.05237 (2019) - [i12]Chen Qu, Liu Yang, Minghui Qiu, Yongfeng Zhang, Cen Chen, W. Bruce Croft, Mohit Iyyer:
Attentive History Selection for Conversational Question Answering. CoRR abs/1908.09456 (2019) - [i11]Keping Bi, Qingyao Ai, Yongfeng Zhang, W. Bruce Croft:
Conversational Product Search Based on Negative Feedback. CoRR abs/1909.02071 (2019) - [i10]Qingyao Ai, Yongfeng Zhang, Keping Bi, W. Bruce Croft:
Explainable Product Search with a Dynamic Relation Embedding Model. CoRR abs/1909.07212 (2019) - [i9]Shaoyun Shi, Hanxiong Chen, Min Zhang, Yongfeng Zhang:
Neural Logic Networks. CoRR abs/1910.08629 (2019) - 2018
- [j2]Qingyao Ai, Vahid Azizi, Xu Chen, Yongfeng Zhang:
Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation. Algorithms 11(9): 137 (2018) - [j1]Yongfeng Zhang, Yi Zhang, Min Zhang:
Report on EARS'18: 1st International Workshop on ExplainAble Recommendation and Search. SIGIR Forum 52(2): 125-131 (2018) - [c33]Yongfeng Zhang, Xu Chen, Qingyao Ai, Liu Yang, W. Bruce Croft:
Towards Conversational Search and Recommendation: System Ask, User Respond. CIKM 2018: 177-186 - [c32]Liu Yang, Minghui Qiu, Chen Qu, Jiafeng Guo, Yongfeng Zhang, W. Bruce Croft, Jun Huang, Haiqing Chen:
Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems. SIGIR 2018: 245-254 - [c31]Pengfei Wang, Ze Yang, Shuzi Niu, Yongfeng Zhang, Lei Zhang, Shaozhang Niu:
Modeling Dynamic Pairwise Attention for Crime Classification over Legal Articles. SIGIR 2018: 485-494 - [c30]Chen Qu, Liu Yang, W. Bruce Croft, Johanne R. Trippas, Yongfeng Zhang, Minghui Qiu:
Analyzing and Characterizing User Intent in Information-seeking Conversations. SIGIR 2018: 989-992 - [c29]Yongfeng Zhang, Yi Zhang, Min Zhang:
SIGIR 2018 Workshop on ExplainAble Recommendation and Search (EARS 2018). SIGIR 2018: 1411-1413 - [c28]Xu Chen, Hongteng Xu, Yongfeng Zhang, Jiaxi Tang, Yixin Cao, Zheng Qin, Hongyuan Zha:
Sequential Recommendation with User Memory Networks. WSDM 2018: 108-116 - [c27]Feida Zhu, Yongfeng Zhang, Neil Yorke-Smith, Guibing Guo, Xu Chen:
IFUP: Workshop on Multi-dimensional Information Fusion for User Modeling and Personalization. WSDM 2018: 804-805 - [i8]Xu Chen, Yongfeng Zhang, Hongteng Xu, Yixin Cao, Zheng Qin, Hongyuan Zha:
Visually Explainable Recommendation. CoRR abs/1801.10288 (2018) - [i7]Yongfeng Zhang, Qingyao Ai, Xu Chen, Pengfei Wang:
Learning over Knowledge-Base Embeddings for Recommendation. CoRR abs/1803.06540 (2018) - [i6]Chen Qu, Liu Yang, W. Bruce Croft, Johanne R. Trippas, Yongfeng Zhang, Minghui Qiu:
Analyzing and Characterizing User Intent in Information-seeking Conversations. CoRR abs/1804.08759 (2018) - [i5]Yongfeng Zhang, Xu Chen:
Explainable Recommendation: A Survey and New Perspectives. CoRR abs/1804.11192 (2018) - [i4]Liu Yang, Minghui Qiu, Chen Qu, Jiafeng Guo, Yongfeng Zhang, W. Bruce Croft, Jun Huang, Haiqing Chen:
Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems. CoRR abs/1805.00188 (2018) - [i3]Qingyao Ai, Vahid Azizi, Xu Chen, Yongfeng Zhang:
Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation. CoRR abs/1805.03352 (2018) - 2017
- [c26]Wenwen Ye, Yongfeng Zhang, Wayne Xin Zhao, Xu Chen, Zheng Qin:
A Collaborative Neural Model for Rating Prediction by Leveraging User Reviews and Product Images. AIRS 2017: 99-111 - [c25]Xu Chen, Yongfeng Zhang, Wayne Xin Zhao, Wenwen Ye, Zheng Qin:
Probabilistic Local Matrix Factorization Based on User Reviews. AIRS 2017: 154-166 - [c24]Xiao Lin, Min Zhang, Yongfeng Zhang:
Joint Factorizational Topic Models for Cross-City Recommendation. APWeb/WAIM (1) 2017: 591-609 - [c23]Xiao Lin, Min Zhang, Yongfeng Zhang, Zhaoquan Gu:
Disparity-Aware Group Formation for Recommendation. AAMAS 2017: 1604-1606 - [c22]Xiao Lin, Min Zhang, Yongfeng Zhang, Yiqun Liu, Shaoping Ma:
Learning and Transferring Social and Item Visibilities for Personalized Recommendation. CIKM 2017: 337-346 - [c21]Yongfeng Zhang, Qingyao Ai, Xu Chen, W. Bruce Croft:
Joint Representation Learning for Top-N Recommendation with Heterogeneous Information Sources. CIKM 2017: 1449-1458 - [c20]Xiao Lin, Min Zhang, Yongfeng Zhang, Zhaoquan Gu, Yiqun Liu, Shaoping Ma:
Boosting Moving Average Reversion Strategy for Online Portfolio Selection: A Meta-learning Approach. DASFAA (2) 2017: 494-510 - [c19]Xiao Lin, Min Zhang, Yongfeng Zhang, Zhaoquan Gu, Yiqun Liu, Shaoping Ma:
Fairness-Aware Group Recommendation with Pareto-Efficiency. RecSys 2017: 107-115 - [c18]Xu Chen, Yongfeng Zhang, Qingyao Ai, Hongteng Xu, Junchi Yan, Zheng Qin:
Personalized Key Frame Recommendation. SIGIR 2017: 315-324 - [c17]Qingyao Ai, Yongfeng Zhang, Keping Bi, Xu Chen, W. Bruce Croft:
Learning a Hierarchical Embedding Model for Personalized Product Search. SIGIR 2017: 645-654 - [c16]Qi Zhao, Yongfeng Zhang, Yi Zhang, Daniel Friedman:
Multi-Product Utility Maximization for Economic Recommendation. WSDM 2017: 435-443 - [i2]Liu Yang, Hamed Zamani, Yongfeng Zhang, Jiafeng Guo, W. Bruce Croft:
Neural Matching Models for Question Retrieval and Next Question Prediction in Conversation. CoRR abs/1707.05409 (2017) - 2016
- [c15]Xu Chen, Zheng Qin, Yongfeng Zhang, Tao Xu:
Learning to Rank Features for Recommendation over Multiple Categories. SIGIR 2016: 305-314 - [c14]Xu Chen, Pengfei Wang, Zheng Qin, Yongfeng Zhang:
HLBPR: A Hybrid Local Bayesian Personal Ranking Method. WWW (Companion Volume) 2016: 21-22 - [c13]Yongfeng Zhang, Qi Zhao, Yi Zhang, Daniel Friedman, Min Zhang, Yiqun Liu, Shaoping Ma:
Economic Recommendation with Surplus Maximization. WWW 2016: 73-83 - 2015
- [c12]Yongfeng Zhang, Min Zhang, Yiqun Liu, Tat-Seng Chua, Yi Zhang, Shaoping Ma:
Task-based recommendation on a web-scale. IEEE BigData 2015: 827-836 - [c11]Yongfeng Zhang, Yunzhi Tan, Min Zhang, Yiqun Liu, Tat-Seng Chua, Shaoping Ma:
Catch the Black Sheep: Unified Framework for Shilling Attack Detection Based on Fraudulent Action Propagation. IJCAI 2015: 2408-2414 - [c10]Yuan Wang, Jie Liu, Yalou Huang, Yongfeng Zhang, Yi Zhang, Xintong Zhang:
Exploration of Semantic-aware Approach for Contextual Suggestion Using Knowledge from The Open Web. TREC 2015 - [c9]Yongfeng Zhang, Min Zhang, Yi Zhang, Guokun Lai, Yiqun Liu, Honghui Zhang, Shaoping Ma:
Daily-Aware Personalized Recommendation based on Feature-Level Time Series Analysis. WWW 2015: 1373-1383 - [i1]Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma:
Boost Phrase-level Polarity Labelling with Review-level Sentiment Classification. CoRR abs/1502.03322 (2015) - 2014
- [c8]Yongfeng Zhang, Min Zhang, Yi Zhang, Yiqun Liu, Shaoping Ma:
Understanding the Sparsity: Augmented Matrix Factorization with Sampled Constraints on Unobservables. CIKM 2014: 1189-1198 - [c7]Yongfeng Zhang, Guokun Lai, Min Zhang, Yi Zhang, Yiqun Liu, Shaoping Ma:
Explicit factor models for explainable recommendation based on phrase-level sentiment analysis. SIGIR 2014: 83-92 - [c6]Yongfeng Zhang, Haochen Zhang, Min Zhang, Yiqun Liu, Shaoping Ma:
Do users rate or review?: boost phrase-level sentiment labeling with review-level sentiment classification. SIGIR 2014: 1027-1030 - 2013
- [c5]Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma:
A general collaborative filtering framework based on matrix bordered block diagonal forms. HT 2013: 219-224 - [c4]Yunzhi Tan, Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma:
A Unified Framework for Emotional Elements Extraction Based on Finite State Matching Machine. NLPCC 2013: 60-71 - [c3]Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma:
Improve collaborative filtering through bordered block diagonal form matrices. SIGIR 2013: 313-322 - [c2]Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma, Shi Feng:
Localized matrix factorization for recommendation based on matrix block diagonal forms. WWW 2013: 1511-1520 - 2010
- [c1]Ting Yao, Min Zhang, Yiqun Liu, Shaoping Ma, Yongfeng Zhang, Liyun Ru:
Investigating Characteristics of Non-click Behavior Using Query Logs. AIRS 2010: 85-96
Coauthor Index
[j21] [j18] [c122] [c119] [c115] [i98] [i91] [i90] [j14] [j12] [c112] [c110] [c108] [c106] [c105] [i74] [i72] [i70] [i69] [i66] [i65] [i64] [i61] [i60] [c102] [c97] [c96] [c95] [c94] [c92] [c90] [c89] [i59] [i55] [i54] [i53] [i52] [i51] [i50] [c85] [c83] [c77] [c74] [c72] [c69] [c68] [c66] [i45] [i42] [i40] [i38] [i37] [i36] [i34] [i33] [c62] [c58] [c56] [c55] [i27] [i25] [i24] [i19] [c35]
[j21] [j18] [c122] [c119] [c115] [c114] [i91] [i90] [i85] [i81] [j14] [j12] [j9] [c110] [c108] [c107] [c106] [c105] [c104] [i74] [i72] [i70] [i69] [i66] [i65] [i60] [c100] [c97] [c89] [i55] [i51] [i50] [i47] [c85] [c78] [c77] [c76] [c66] [i44] [i42] [i37] [i36] [i34] [i33] [i32] [c60] [c58] [c56] [i27] [i26] [i24] [c35]
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-11-29 01:15 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
