Hanchen Zhang
Hanchen Zhang has 3 papers in our library, in 2023–2026; often with Xiao Liu, Hanyu Lai, Hao Yu.
OpenAlex · ORCID · h-index 24 · 69 works · 1,822 citations OpenAlex, 2026-10-14
📄 3 works in our library · 🔗 Cited 428 times in our library · ⭐ Paper Stars ranking: #3734
Affiliations
🏛️Chinese Academy of SciencesBeijing ·
China2022–2026 · 31 papers🔬Institute of ChemistryBeijing ·
China2022–2026 · 30 papers🔬Beijing National Laboratory for Molecular SciencesBeijing ·
China2022–2026 · 28 papers🎓Ningxia UniversityYinchuan ·
China2020–2026 · 10 papers🎓Sun Yat-sen UniversityGuangzhou ·
China2020–2026 · 4 papers🎓Tsinghua UniversityBeijing ·
China2024–2026 · 3 papers🏥Sixth Affiliated Hospital of Sun Yat-sen UniversityGuangzhou ·
China2022–2026 · 2 papers🎓Sichuan UniversityChengdu ·
China2026 · 1 paper🎓University of Chinese Academy of SciencesBeijing ·
China2022–2025 · 16 papers🔬State Key Laboratory of Polymer Physics and ChemistryBeijing ·
China2022–2025 · 8 papers
Fields, topics and concepts
📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksArtificial Intelligence · 2 worksArts and Humanities · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work
Works by year
2020s
Papers
- AgentBench: Evaluating LLMs as Agents (2023 · 432 citations)
Agent-style applications built on large language models are spreading quickly, yet there has been no standard way to measure how well a model performs as an autonomous agent. - AutoWebGLM: A Large Language Model-based Web Navigating Agent (2024 · 96 citations)
Web agents built on LLMs often fail on real websites. Pages are long and noisy, the set of possible browser actions is broad, and open-web tasks are hard to plan. Existing agents also struggle to recover from their own mistakes. The authors address this with AutoWebGLM, an open agent fine-tuned from ChatGLM3-6B. It… - KARL: Reinforcement Learning for LLM Agents on Multi-Turn Knowledge-Intensive Agentic Tasks (2026)
LLM agents often handle knowledge-heavy tasks poorly because they consume external information passively. Retrieval is either fixed in advance or tuned only for single-turn question answering. KARL (Knowledge-Augmented Reinforcement Learning) addresses this for multi-turn work over structured sources such as…
Co-authors here
- Xiao Liu ×3
- Hanyu Lai ×2
- Hao Yu ×2
- Jie Tang ×2
- Yifan Xu ×2
- Yuxiao Dong ×2
- Shudan Zhang
- Shuntian Yao
- Xiang Deng
- Xiaohan Zhang
- Xuanyu Lei
- Xueqiao Sun
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
- ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD): KDD 2024
Cited by
Updated
This page in Markdown → https://md.research.elamur.ai/free/en/authors/hanchen-zhang/