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Xunjian Yin

Xunjian Yin has 2 papers in our library, in 2025, most of them on Language models & pretraining, Text generation, Evaluation & benchmarks; often with Arman Cohan, Mark Gerstein, Muyang Ye.

2 papers in our library · 2025

OpenAlex · ORCID · h-index 5 · 28 works · 183 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 165 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #5990

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

🎓Peking UniversityBeijing · China2022–2026 · 18 paperscurrent🎓Duke UniversityDurham · United States2026 · 4 papersEmploymentcurrent🎓University of California, Santa BarbaraSanta Barbara · United States2024–2026 · 2 paperscurrent

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 8The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 workMaterials Science · 1 workComputational Theory and Mathematics · 1 workComputer Vision and Pattern Recognition · 1 workMaterials Chemistry · 1 work

🧭 Topics 4Research subjects and languages the work is about.Evaluation & benchmarks · 1 workText generation · 1 workLanguage models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. LLM-based NLG Evaluation: Current Status and Challenges (2025 · 153 citations)
    Judging natural language generation is difficult because a good output has no single correct form and must satisfy several quality criteria at once.
  2. ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning (2025 · 15 citations)
    Large language models often fail at multi-step chemistry problems. They misuse domain formulas, choose wrong constants or units, and make arithmetic slips that carry through later steps. They also write faulty Python for calculations. Earlier fixes such as StructChem prompting or self-reflection rely on fixed…

All works

5 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. LLM-based NLG Evaluation: Current Status and ChallengesComputational LinguisticsMingqi Gao, Xinyu Hu, Xunjian Yin, et al.2025 · 153 citations
  2. Human-like Summarization Evaluation with ChatGPT ↗arXiv:2304.02554 · no summary yetMingqi Gao et al.2023 · 128 citations
  3. ChemAgent: Self-updating Library in Large Language Models Improves Chemical ReasoningarXiv:2501.06590Xiangru Tang, Tianyu Hu, Muyang Ye, et al.2025 · 15 citations
  4. Exploring Context-Aware Evaluation Metrics for Machine Translation ↗Findings of the Association for Computational Linguistics: EMNLP 2023 · no summary yetXinyu Hu, Xunjian Yin, Xiaojun Wan2023 · 4 citations
  5. LEDOM: Reverse Language Model ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetXunjian Yin et al.2026

 Co-authors here

12 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 165 times (of the 149,439 papers whose bibliographies we read); 32 citing papers with a page here →.

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