Zhang, Weinan

Texygen: A Benchmarking Platform for Text Generation Models

Zhu, Y., Lu, S., Zheng, L., Guo, J., Zhang, W., Wang, J., & Yu, Y. (2018) · The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval

Topic ModelingNatural Language Processing Techniques

Cited by 408

How Can Recommender Systems Benefit from Large Language Models: A Survey

Lin, J., Dai, X., Xi, Y., Liu, W., Chen, B., Zhang, H., Liu, Y., Wu, C., Li, X., Zhu, C., et al. (2025) · ACM Transactions on Information Systems

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 242

Dynamically Fused Graph Network for Multi-hop Reasoning

Qiu, L., Xiao, Y., Qu, Y., Zhou, H., Li, L., Zhang, W., & Yu, Y. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Topic ModelingMultimodal Machine Learning Applications

Cited by 181

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

Liu, B., Zhu, C., Li, G., Zhang, W., Lai, J., Tang, R., He, X., Li, Z., & Yu, Y. (2020) · Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 171

Interactive collaborative filtering

Zhao, X., Zhang, W., & Wang, J. (2013) · Proceedings of the 22nd ACM international conference on Information & Knowledge Management

Recommender Systems and TechniquesAdvanced Bandit Algorithms Research

Cited by 165

Goal-Conditioned Reinforcement Learning: Problems and Solutions

Liu, M., Zhu, M., & Zhang, W. (2022) · Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 115

Glancing Transformer for Non-Autoregressive Neural Machine Translation

Qian, L., Zhou, H., Bao, Y., Wang, M., Qiu, L., Zhang, W., Yu, Y., & Li, L. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 108

Vision-Language Foundation Models as Effective Robot Imitators

Li, X., Liu, M., Zhang, H., Yu, C., Xu, J., Wu, H., Cheang, C., Jing, Y., Zhang, W., Liu, H., et al. (2023) · arXiv

Robot Manipulation and LearningMultimodal Machine Learning Applications

Cited by 28

Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Feng, X., Wan, Z., Wen, M., McAleer, S. M., Wen, Y., Zhang, W., & Wang, J. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4

Understanding and Optimizing Agentic Workflows via Shapley value

Yang, Y., Huang, B., Qi, S., Feng, C., Hu, H., Zhu, Y., Hu, J., Zhao, H., He, Z., Liu, X., et al. (2025) · arXiv

AI-based Problem Solving and PlanningGame Theory and Voting Systems

Cited by 2

GenSim2: Scaling Robot Data Generation with Multi-modal and Reasoning LLMs

Hua, P., Liu, M., Macaluso, A., Lin, Y., Zhang, W., Xu, H., & Wang, L. (2024) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 2

Understanding Agent Scaling in LLM-Based Multi-Agent Systems via Diversity

Yang, Y., Qu, C., Wen, M., Shi, L., Wen, Y., Zhang, W., Wierman, A., & Gu, S. (2026) · arXiv

Multi-Agent Systems and NegotiationReinforcement Learning in Robotics

Cited by 1

Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering

Zhou, C., Chai, H., Chen, W., Guo, Z., Shan, R., Song, Y., Xu, T., Yang, Y., Yu, A., Zhang, W., et al. (2026) · arXiv

Artificial Intelligence ApplicationsAI-based Problem Solving and Planning

Cited by 1

Your Agent May Misevolve: Emergent Risks in Self-evolving LLM Agents

Shao, S., Ren, Q., Qian, C., Wei, B., Guo, D., Yang, J., Song, X., Zhang, L., Zhang, W., Liu, D., et al. (2025) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 1

Evolutionary Perspectives on the Evaluation of LLM-Based AI Agents: A Comprehensive Survey

Zhu, J., Zhu, M., Rui, R., Shan, R., Zheng, C., Chen, B., Xi, Y., Lin, J., Liu, W., Tang, R., et al. (2025) · arXiv

Speech and dialogue systemsArtificial Intelligence Applications

Cited by 0

Agent-Dice: Disentangling Knowledge Updates via Geometric Consensus for Agent Continual Learning

Wu, Z., Lou, X., Ma, X., Li, Y., Liu, W., Zhang, W., Wang, J., & Zhang, Z. (2026) · arXiv

Domain Adaptation and Few-Shot LearningReinforcement Learning in Robotics

Cited by 0

PARL-MT: Learning to Call Functions in Multi-Turn Conversation with Progress Awareness

Chai, H., Cao, Z., Ran, M., Yang, Y., Lin, J., Peng, X., Wang, H., Ding, R., Wan, Z., Wen, M., et al. (2025) · arXiv

Speech and dialogue systemsNatural Language Processing Techniques

Cited by 0

SkillProbe: Security Auditing for Emerging Agent Skill Marketplaces via Multi-Agent Collaboration

Guo, Z., Chen, Z., Nie, X., Lin, J., Zhou, Y., & Zhang, W. (2026) · arXiv

Adversarial Robustness in Machine LearningAccess Control and Trust

Cited by 0

MARFT: Multi-Agent Reinforcement Fine-Tuning

Liao, J., Wen, M., Wang, J., & Zhang, W. (2025) · arXiv

Reinforcement Learning in RoboticsMulti-Agent Systems and Negotiation

Cited by 0

Holos: A Web-Scale LLM-Based Multi-Agent System for the Agentic Web

Nie, X., Guo, Z., Cui, Z., Yang, J., Chen, Z., De, L., Zhang, Y., Liao, J., Huang, B., Yang, Y., et al. (2026) · arXiv

Multi-Agent Systems and NegotiationArtificial Intelligence Applications

Cited by 0