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Huifeng Yin

Huifeng Yin has 3 papers in our library, in 2025–2026, most of them on Summarization, Reasoning, Efficient models & compression; often with Fei Huang, Kuan Li, Litu Ou.

3 papers in our library · 2025–2026

OpenAlex · h-index 0 · 1 works · 0 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 33 times in our library · ⭐ Paper Stars ranking: #8302

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

🏢Alibaba GroupGeorge Town · Cayman Islands2026 · 1 papercurrent🏢Alibaba GroupHangzhou · China2026 · 1 papercurrent

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 6The 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 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Summarization · 1 workEfficient models & compression · 1 workReasoning · 1 work

 Works by year

2020s

20261 paper20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. ReSum: Unlocking Long-Horizon Search Intelligence via Context Summarization (2025 · 26 citations)
    Web agents built on LLMs often fail on hard multi-hop questions. The ReAct loop keeps adding every search result to the prompt, so the context window fills up before the agent finds the answer. Earlier fixes such as MEM1 or MemAgent change the model's architecture and require full retraining. ReSum avoids this with a…
  2. Marco-o1 v2: Towards Widening The Distillation Bottleneck for Reasoning Models (2025 · 8 citations)
    Small models are often taught to reason by fine-tuning them on long chain-of-thought (CoT) traces from large reasoning models such as DeepSeek-R1.
  3. BrowseConf: Confidence-Guided Test-Time Scaling for Web Agents (2026)
    The paper asks whether LLM-based web search agents can meaningfully report how sure they are after long chains of browsing and reasoning.

 Co-authors here

12 of 23 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 33 times (of the 149,439 papers whose bibliographies we read); 14 citing papers with a page here →.

Updated

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