--- title: "Yao Hu — author profile and papers — Elamur Research" description: "Yao Hu, Xiaohongshu (Little Red Book): 8 papers on Elamur Research (2024–2026), h-index 1 — affiliations, topics, co-authors and who…" canonical: "https://research.elamur.ai/free/en/authors/yao-hu/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yao-hu/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yao Hu # Yao Hu Yao Hu has 8 papers in our library, in 2024–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Yan Gao](https://md.research.elamur.ai/free/en/authors/yan-gao/), [Chengqiang Lu](https://md.research.elamur.ai/free/en/authors/chengqiang-lu/), [Daoxin Zhang](https://md.research.elamur.ai/free/en/authors/daoxin-zhang/). 8 papers in our library · 2024–2026 [OpenAlex](https://openalex.org/A5139727495) · [**h-index 1**](https://openalex.org/authors/A5139727495) · [5 works](https://openalex.org/works?filter=author.id:A5139727495) · [1 citations](https://openalex.org/works?filter=author.id:A5139727495&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 8 works in our library](https://md.research.elamur.ai/free/en/authors/yao-hu/#papers) · [🔗 Cited 89 times in our library](https://md.research.elamur.ai/free/en/authors/yao-hu/cited-by/) · [⭐ Paper Stars ranking: #6496](https://md.research.elamur.ai/free/en/paper-stars/page/65/#star-6496) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Yao+Hu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yao+Hu) · [dblp](https://dblp.org/search?q=Yao+Hu) · [ACL Anthology](https://aclanthology.org/search/?q=Yao+Hu) ## Affiliations [🏢**Xiaohongshu (Little Red Book)** Shanghai · China 2026 · 5 papers*current*](https://md.research.elamur.ai/free/en/companies/xiaohongshu-little-red-book/) 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 6 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 8 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 8 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 8 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 8 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Information Systems · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) 🧭 Topics 4 Research subjects and languages the work is about.[Language models & pretraining · 4 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) ## Works by year ### 2020s [**2026** 6 papers](https://md.research.elamur.ai/free/en/authors/yao-hu/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/yao-hu/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/yao-hu/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM Inference](https://md.research.elamur.ai/free/en/papers/yang-2024-pyramidinfer-pyramid-kv-cache-compression/)** *(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](https://md.research.elamur.ai/free/en/papers/zhang-2025-law-capacity-gap-distilling-language/)** *(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. **[LLM-Powered Benchmark Factory: Reliable, Generic, and Efficient](https://md.research.elamur.ai/free/en/papers/yuan-2026-llm-powered-benchmark-factory-reliable/)** *(2026 · 3 citations)* With tens of thousands of new LLMs appearing each season, practitioners need custom benchmarks to choose models for their tasks. 4. **[Anti-Length Shift: Dynamic Outlier Truncation for Training Efficient Reasoning Models](https://md.research.elamur.ai/free/en/papers/wu-2026-anti-length-shift-dynamic-outlier/)** *(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. **[Robust Tool Use via Fission-GRPO: Learning to Recover from Execution Errors](https://md.research.elamur.ai/free/en/papers/zhang-2026-robust-tool-use-fission-grpo/)** *(2026 · 1 citation)* Small tool-calling LLMs handle multi-turn tasks poorly once a tool call fails. Instead of reading the error message and adjusting, they often repeat the same invalid call until the dialogue breaks down. On BFCL v4 Multi-Turn, Qwen3-8B recovers in only about 20% of such cases, while Claude Sonnet 4 recovers in over… 6. **[SPARD: Self-Paced Curriculum for RL Alignment via Integrating Reward Dynamics and Data Utility](https://md.research.elamur.ai/free/en/papers/zhi-2026-spard-self-paced-curriculum-rl/)** *(2026 · 1 citation)* LLM post-training increasingly targets open-ended tasks, where rewards come from several criteria scored by an LLM judge. 7. **[Leveraging Outline-Optimized Generative Interactions and Critique for Self-Refining Outlines with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-leveraging-outline-optimized-generative-interactions/)** *(2026)* Small language models struggle to produce hierarchical outlines for Wikipedia-style expository articles. Their outlines tend to skip levels, omit important branches and distribute depth poorly. Existing remedies such as STORM, OmniThink or RAPID rely on costly multi-turn LLM interaction or fixed refinement… 8. **[Pause or Fabricate? Training Language Models for Grounded Reasoning](https://md.research.elamur.ai/free/en/papers/qiu-2026-pause-or-fabricate-training-language/)** *(2026)* The paper examines a failure mode the authors call ungrounded reasoning. When a question lacks a needed fact, a language model often notices the gap early but then invents a value and reasons confidently to a wrong answer. The authors argue that the cause is weak awareness of when valid inference is possible, not… ## Co-authors here 12 of 34 co-authors with a page, the most papers together first. - [Yan Gao](https://md.research.elamur.ai/free/en/authors/yan-gao/) ×4 - [Chengqiang Lu](https://md.research.elamur.ai/free/en/authors/chengqiang-lu/) ×2 - [Daoxin Zhang](https://md.research.elamur.ai/free/en/authors/daoxin-zhang/) ×2 - [Weiming Lu](https://md.research.elamur.ai/free/en/authors/weiming-lu/) ×2 - [Yiwu](https://md.research.elamur.ai/free/en/authors/yiwu/) ×2 - [Yongliang Shen](https://md.research.elamur.ai/free/en/authors/yongliang-shen/) ×2 - [Bin Liang](https://md.research.elamur.ai/free/en/authors/bin-liang/) - [Chen Zhang](https://md.research.elamur.ai/free/en/authors/chen-zhang/) - [Dawei Song](https://md.research.elamur.ai/free/en/authors/dawei-song/) - [Defu Lian](https://md.research.elamur.ai/free/en/authors/defu-lian/) - [Fei Zhao](https://md.research.elamur.ai/free/en/authors/fei-zhao/) - [Hai Zhao](https://md.research.elamur.ai/free/en/authors/hai-zhao/) ## 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)](https://md.research.elamur.ai/free/en/venues/acl/) ×6: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×5, [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×2: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/), [Findings of the Association for Computational Linguistics 2024](https://md.research.elamur.ai/free/en/venues/findings/2024/) ## Cited by Papers of our library cite their works 89 times (of the 149,439 papers whose bibliographies we read); [15 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yao-hu/cited-by/). Updated 1 November 2026