Junzhe Wang
Junzhe Wang has 4 papers in our library, in 2023–2026, most of them on Language models & pretraining; often with Ming Zhang, Zhiheng Xi, Bichen Wang.
OpenAlex · ORCID · h-index 8 · 27 works · 1,049 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 427 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #2083
Affiliations
Fields, topics and concepts
📚 Shelves 10The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksSafety Research · 1 workSocial Sciences · 1 workPsychology · 1 workApplied Psychology · 1 workExperimental and Cognitive Psychology · 1 workInformation Systems · 1 work
🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work
💡 Concepts 1Key ideas and methods explained on our concept pages.Large language models · 1 work
Works by year
2020s
Papers
- The Rise and Potential of Large Language Model Based Agents: A Survey (2023 · 1,272 citations)
This 2023 survey from the Fudan NLP Group maps the young field of agents built on large language models. The authors argue that earlier agent research mostly tuned algorithms for narrow skills, such as symbolic reasoning or board games like Go and Chess. What the field lacked was a general base model that agents… - LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models (2026 · 3 citations)
Fixed public test sets can leak into training corpora and be overfitted, so leaderboard scores may overstate real LLM ability. - Psychological Counseling Cannot Be Achieved Overnight: Automated Psychological Counseling Through Multi-Session Conversations (2026 · 2 citations)
Most LLM-based counseling systems treat therapy as a single conversation. Real therapy such as Cognitive Behavioral Therapy (CBT) unfolds over many visits, with goals revised as the client changes. This paper frames automated counseling as a longitudinal task made of three parts: memory extraction, goal planning and… - Enhancing LLM-based Search Agents via Contribution Weighted Group Relative Policy Optimization (2026)
Search agents built on LLMs learn to query external engines during multi-round reasoning, but reinforcement learning for such agents faces a dilemma.
All works
- The Rise and Potential of Large Language Model Based Agents: A SurveyScience China Information SciencesZhiheng Xi, Wenxiang Chen, Xin Guo, et al.2023 · 1,272 citations
- Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning ↗arXiv:2402.05808 · no summary yetZhiheng Xi et al.2024 · 36 citations
- AgentGym: Evolving Large Language Model-based Agents across Diverse Environments ↗arXiv:2406.04151 · no summary yetZhiheng Xi et al.2024 · 33 citations
- LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Ming Zhang, Yujiong Shen, Jingyi Deng, et al.2026 · 3 citations
- Psychological Counseling Cannot Be Achieved Overnight: Automated Psychological Counseling Through Multi-Session ConversationsFindings of the Association for Computational LinguisticsBichen Wang, Junzhe Wang, Yixin Sun, et al.2026 · 2 citations
- Enhancing LLM-based Search Agents via Contribution Weighted Group Relative Policy OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Junzhe Wang, Zhiheng Xi, Yajie Yang, et al.2026
- AgentGym2: Benchmarking Large Language Model Agents in De-Idealized Real-World Environments ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetZhiheng Xi et al.2026
Co-authors here
- Ming Zhang ×2
- Zhiheng Xi ×2
- Bichen Wang
- Bing Qin
- Enyu Zhou
- Hao Luo
- Jingqi Tong
- Qi Zhang
- Rui Zheng
- Senjie Jin
- Shichun Liu
- Shihan Dou
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×3: ACL 2026 ×2
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
- Science China Information Sciences: Science China Information Sciences 2023
Cited by
Updated
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