🧑‍🔬 Li Lin

🏛️ Affiliations

🎓Wuhan University of TechnologyWuhan · China2009–2026 · 231 paperscurrent🎓Peking UniversityBeijing · China2022–2026 · 3 paperscurrent🏢Alibaba GroupHangzhou · China2021–2026 · 2 paperscurrent🎓Duke UniversityDurham · United States2026 · 1 papercurrent🏥Shenzhen Children's HospitalShenzhen · China2026 · 1 papercurrent🎓Beihang UniversityBeijing · China2008–2025 · 10 papers🎓North China Electric Power UniversityBeijing · China2004–2023 · 6 papers🎓Xiamen UniversityXiamen · China2014–2025 · 5 papers🎓Hefei University of TechnologyHefei · China2010–2024 · 5 papers🎓Qinghai Normal UniversityXining · China2016–2023 · 5 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 78 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

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

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. HAD: HAllucination Detection Language Models Based on a Comprehensive Hallucination Taxonomy (2026 · 1 citation)
   Large language models often produce fluent text that is wrong or that drifts from the given instruction or input.
2. LEDOM: Reverse Language Model (2026)
   Standard autoregressive language models are trained only in the left-to-right direction. The authors ask what happens if the opposite factorization is trained at scale, with each token predicted from the text that follows it. They build LEDOM, a purely right-to-left decoder-only model at 2B and 7B parameters. It is…
3. Minos: A Multimodal Evaluation Model for Bidirectional Generation Between Image and Text (2026)
   Automatic judging of multimodal outputs is still unreliable. Classic metrics often disagree with human ratings, need references, or only work for one task. Existing MLLM-based judges such as LLaVA-Critic and UnifiedReward train on large but loosely filtered data and do not handle both image-to-text (I2T) and…

All works

5 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. TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models ↗Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yetJing Xiong et al.2023 · 21 citations
2. An External Knowledge Enhanced Multi-label Charge Prediction Approach with Label Number Learning ↗arXiv:1907.02205 · no summary yetDuan Wei, Li Lin2019 · 11 citations
3. HAD: HAllucination Detection Language Models Based on a Comprehensive Hallucination TaxonomyAnnual Meeting of the Association for Computational Linguistics (ACL)Fan Xu, Xinyu Hu, Zhenghan Yu, et al.2026 · 1 citation
4. LEDOM: Reverse Language ModelAnnual Meeting of the Association for Computational Linguistics (ACL)Xunjian Yin, Sitao Cheng, Yuxi Xie, et al.2026
5. Minos: A Multimodal Evaluation Model for Bidirectional Generation Between Image and TextFindings of the Association for Computational LinguisticsJunzhe Zhang, Huixuan Zhang, Xinyu Hu, et al.2026

🤝 Co-authors here

12 of 17 co-authors with a page, the most papers together first.

• Xiaojun Wan ×3
• Xinyu Hu ×3
• Fan Xu
• Huixuan Zhang
• Jinjie Gu
• Junzhe Zhang
• Liangming Pan
• Mingqi Gao
• Shi Qiu
• Sitao Cheng
• Wei Zhou
• William Yang Wang

Venues

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

• Annual Meeting of the Association for Computational Linguistics (ACL) ×2: ACL 2026 ×2
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
• Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

🔗 Cited by

Papers of our library cite their works 92 times (of the 149,439 papers whose bibliographies we read); 15 citing papers with a page here →.

Updated 2 November 2026

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