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Jianfeng Cai

Jianfeng Cai has 2 papers in our library, in 2026; often with H.S. Che, Houqiang Li, Jinhua Zhu.

2 papers in our library · 2026

OpenAlex · h-index 0 · 2 works · 0 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 42 times in our library · ⭐ Paper Stars ranking: #8042

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

🎓University of Science and Technology of ChinaHefei · 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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Kimi K3: Open Frontier Intelligence (2026 · 40 citations)
    Open-weight LLMs have advanced quickly in reinforcement learning and test-time reasoning. However, most still sit near the 1T-parameter scale, so their pre-trained base models fall behind proprietary systems. Kimi K3 scales both pre-training and RL. It is a natively multimodal Mixture-of-Experts model with 2.8T total…
  2. Bias Fitting to Mitigate Length Bias of Reward Model in RLHF (2026 · 2 citations)
    Reward models used in RLHF often give higher scores to longer answers whether or not those answers are better.

 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 42 times (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated

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