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Kunlun Zhu

Kunlun Zhu has 3 papers in our library, in 2023–2025, most of them on Language models & pretraining; often with Dingling Xu, Haofei Yu, Nan Zhang.

3 papers in our library · 2023–2025

OpenAlex · ORCID · h-index 5 · 24 works · 350 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 564 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #3305

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

🎓University of Illinois Urbana-ChampaignUrbana · United States2024–2026 · 12 paperscurrent🎓Tsinghua UniversityBeijing · China2023 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksInformation Systems · 2 works

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work

 Works by year

2020s

20251 paper20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs (2023 · 589 citations)
    Open-source LLMs such as LLaMA are weak at tool use: picking and calling external APIs to carry out a user request. Closed models like ChatGPT handle this far better. The paper presents ToolLLM, a pipeline that covers data, training and evaluation.
  2. RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework (2025 · 34 citations)
    Testing RAG systems in specialised fields such as law, finance or medicine is hard. Building expert-annotated, domain-specific test sets is expensive and raises privacy issues, and lexical metrics like BLEU or ROUGE-L judge long answers poorly. RAGEval addresses this by generating evaluation data automatically.…
  3. ResearchTown: Simulator of Human Research Community (2024 · 23 citations)
    Can a community of LLM agents reproduce how human scientists produce and assess research? The authors address this with ResearchTown, a multi-agent simulator that models a research community as an agent-data graph.

All works

4 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIsarXiv:2307.16789Yujia Qin, Shihao Liang, Yining Ye, et al.2023 · 589 citations
  2. RAGEval: Scenario Specific RAG Evaluation Dataset Generation FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Kunlun Zhu, Yifan Luo, Dingling Xu, et al.2025 · 34 citations
  3. ResearchTown: Simulator of Human Research CommunityarXiv:2412.17767Haofei Yu, Zhaochen Hong, Zirui Cheng, et al.2024 · 23 citations
  4. SafeScientist: Toward Risk-Aware Scientific Discoveries by LLM Agents ↗arXiv:2505.23559 · no summary yetKunlun Zhu et al.2025 · 8 citations

 Co-authors here

12 of 20 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 564 times (of the 149,439 papers whose bibliographies we read); 132 citing papers with a page here →.

Updated

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