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Junwei Yang

Junwei Yang has 2 papers in our library, in 2025–2026; often with Bohan Wu, Junyu Luo, Tianyang Han.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 4 · 10 works · 38 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 58 times in our library · ⭐ Paper Stars ranking: #7456

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Beihang UniversityBeijing · China2023–2025 · 3 paperscurrent🏛️Chinese Academy of SciencesBeijing · China2025 · 1 papercurrent🔬Institute of PhysicsBeijing · China2025 · 1 papercurrent🎓Nanjing UniversityNanjing · China2025 · 1 papercurrent🎓Nanjing University of Posts and TelecommunicationsNanjing · China2025 · 1 papercurrent🎓Southwest Petroleum UniversityChengdu · China2025 · 1 papercurrent🎓University of Chinese Academy of SciencesBeijing · China2025 · 1 papercurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksArts and Humanities · 1 workLanguage and Linguistics · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Large Language Model Agent: A Survey on Methodology, Applications and Challenges (2025 · 62 citations)
    Work on LLM-based agents has grown quickly but remains scattered. Existing reviews tend to cover one slice, such as games, deployment settings, multimodality or security, or they give broad overviews without a method-level breakdown. Luo et al. address this with a survey built around how agents are engineered. Its…
  2. Failure makes the agent stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions (2026 · 2 citations)
    Tool-using LLMs are usually trained to get a single call right. When a call fails in a multi-turn exchange, they often repeat the error instead of recovering. Prompt-based self-reflection does little to fix this. The authors make error repair an explicit, trainable action instead. After a failed call, the agent…

 Co-authors here

9 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 58 times (of the 149,439 papers whose bibliographies we read); 17 citing papers with a page here →.

Updated

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