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Yan Gao

Yan Gao has 5 papers in our library, in 2024–2026, most of them on Language models & pretraining, Reasoning, Efficient models & compression; often with Yao Hu, Chengqiang Lu, Yiwu.

5 papers in our library · 2024–2026

OpenAlex · h-index 1 · 4 works · 3 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 116 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6303

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

🏢Xiaohongshu (Little Red Book)Shanghai · China2026 · 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 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 5 worksComputer Science · 5 worksArtificial Intelligence · 5 worksLanguage and Linguistics · 5 worksComputer Vision and Pattern Recognition · 3 worksInformation Systems · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 2 worksEfficient models & compression · 1 workReasoning · 1 work

 Works by year

2020s

20262 papers20252 papers20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM Inference (2024 · 91 citations)
    Serving LLMs at scale is limited by GPU memory, and the KV cache often takes far more memory than the model weights.
  2. Towards the Law of Capacity Gap in Distilling Language Models (2025 · 27 citations)
    Knowledge distillation compresses a large teacher language model into a smaller student. However, a bigger teacher does not always produce a better student. This "curse of capacity gap" means the best teacher size for a given student is usually found by distilling from many teachers, which is too costly for LLMs. The…
  3. WideSearch: Benchmarking Agentic Broad Info-Seeking (2025 · 20 citations)
    Many everyday and professional information needs, such as listing every job opening or admission threshold that matches a set of conditions, are hard because of their scale and the need for exactness, not because of deep reasoning.
  4. Anti-Length Shift: Dynamic Outlier Truncation for Training Efficient Reasoning Models (2026 · 1 citation)
    Reasoning models trained with RLVR tend to write very long chains of thought even for easy questions, which makes deployment expensive.
  5. SPARD: Self-Paced Curriculum for RL Alignment via Integrating Reward Dynamics and Data Utility (2026 · 1 citation)
    LLM post-training increasingly targets open-ended tasks, where rewards come from several criteria scored by an LLM judge.

All works

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

  1. PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM InferenceFindings of the Association for Computational LinguisticsDongjie Yang, Xiaodong Han, Yan Gao, et al.2024 · 91 citations
  2. Towards the Law of Capacity Gap in Distilling Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Chen Zhang, Qiuchi Li, Dawei Song, et al.2025 · 27 citations
  3. WideSearch: Benchmarking Agentic Broad Info-SeekingarXiv:2508.07999Ryan Wong, Jiawei Wang, Junjie Zhao, et al.2025 · 20 citations
  4. NL2Formula: Generating Spreadsheet Formulas from Natural Language Queries ↗Findings of the Association for Computational Linguistics: EACL 2024 · no summary yetWei Zhao et al.2024 · 11 citations
  5. Anti-Length Shift: Dynamic Outlier Truncation for Training Efficient Reasoning ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Wei Wu, Liyi Chen, Congxi Xiao, et al.2026 · 1 citation
  6. SPARD: Self-Paced Curriculum for RL Alignment via Integrating Reward Dynamics and Data UtilityAnnual Meeting of the Association for Computational Linguistics (ACL)Xuyang Zhi, Peilun Zhou, Chengqiang Lu, et al.2026 · 1 citation

 Co-authors here

12 of 21 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 116 times (of the 149,439 papers whose bibliographies we read); 27 citing papers with a page here →.

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