| OpenAGI: When llm meets domain experts Y Ge, W Hua, J Ji, J Tan, S Xu, Y Zhang NeurIPS benchmark track 2023, 2023 | 244 | 2023 |
| How to Index Item IDs for Recommendation Foundation Models W Hua, S Xu, Y Ge, Y Zhang SIGIR-AP 2023, 2023 | 104 | 2023 |
| War and peace (waragent): Large language model-based multi-agent simulation of world wars W Hua, L Fan, L Li, K Mei, J Ji, Y Ge, L Hemphill, Y Zhang arXiv preprint arXiv:2311.17227, 2023 | 86 | 2023 |
| The impact of reasoning step length on large language models M Jin, Q Yu, H Zhao, W Hua, Y Meng, Y Zhang, M Du ACL findings 2024, 2024 | 64* | 2024 |
| EntQA: Entity linking as question answering W Zhang, W Hua, K Stratos ICLR spotlight 2022, 2021 | 64 | 2021 |
| Genrec: Large language model for generative recommendation J Ji, Z Li, S Xu, W Hua, Y Ge, J Tan, Y Zhang ECIR 2024, 2023 | 55 | 2023 |
| UP5: Unbiased Foundation Model for Fairness-aware Recommendation W Hua, Y Ge, S Xu, J Ji, Y Zhang EACL 2023, 2023 | 53 | 2023 |
| OpenP5: An Open-Source Platform for Developing, Training, and Evaluating LLM-based Recommender Systems S Xu, W Hua, Y Zhang SIGIR 2024, 386-394, 2024 | 46 | 2024 |
| Tutorial on Large Language Models for Recommendation W Hua, L Li, S Xu, L Chen, Y Zhang RecSys 2023, 1281-1283, 2023 | 39 | 2023 |
| Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers? M Jin, Q Yu, J Huang, Q Zeng, Z Wang, W Hua, H Zhao, K Mei, Y Meng, ... COLING 2025, 558-573, 2024 | 35* | 2024 |
| AIOS: LLM Agent Operating System K Mei, X Zhu, W Xu, W Hua, M Jin, S Xu, R Ye, Y Ge, Y Zhang https://arxiv.org/abs/2403.16971, 35, 2024 | 34* | 2024 |
| NPHardEval: Dynamic benchmark on reasoning ability of large language models via complexity classes L Fan*, W Hua*, L Li, H Ling, Y Zhang ACL 2024, 2023 | 28 | 2023 |
| IDGenRec: LLM-RecSys Alignment with Textual ID Learning J Tan, S Xu, W Hua, Y Ge, Z Li, Y Zhang SIGIR 2024, 355-364, 2024 | 27* | 2024 |
| LLM as OS agents as APPs: Envisioning AISO, agents and the AIOS-agent ecosystem Y Ge, Y Ren, W Hua, S Xu, J Tan, Y Zhang arXiv preprint arXiv:2312.03815, 2023 | 25* | 2023 |
| A scoping review of using Large Language Models (LLMs) to investigate Electronic Health Records (EHRs) L Li, J Zhou, Z Gao, W Hua, L Fan, H Yu, L Hagen, Y Zhang, TL Assimes, ... | 24 | 2024 |
| TrustAgent: Towards Safe and Trustworthy LLM-based Agents W Hua, X Yang, M Jin, Z Li, W Cheng, R Tang, Y Zhang EMNLP findings, 2024, 2024 | 18* | 2024 |
| A Predicate-Function-Argument Annotation of Natural Language for Open-Domain Information eXpression M Sun, W Hua, Z Liu, X Wang, K Zheng, P Li EMNLP 2020, 2020 | 14 | 2020 |
| NPHardEval4V: A Dynamic Reasoning Benchmark of Multimodal Large Language Models L Fan*, W Hua*, X Li*, K Zhu, M Jin, L Li, H Ling, J Chi, J Wang, X Ma, ... arXiv preprint arXiv:2403.01777, 2024 | 13 | 2024 |
| EmojiPrompt: Generative Prompt Obfuscation for Privacy-Preserving Communication with Cloud-based LLMs G Lin*, W Hua*, Z Wang, M Jin, Y Zhang NACCL 2025, 2024 | 13* | 2024 |
| Formal-LLM: Integrating formal language and natural language for controllable llm-based agents Z Li, W Hua, H Wang, H Zhu, Y Zhang arXiv preprint arXiv:2402.00798, 2024 | 13 | 2024 |
Yongfeng ZhangProfessor of Computer Science, Rutgers UniversityEmail verificata su rutgers.edu