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Fanheng Kong

Fanheng Kong has 2 papers in our library, in 2026, most of them on Language models & pretraining, Reasoning, Vision & language; often with Chenyan WU, Daling Wang, Dexian Cai.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 13 · 40 works · 946 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #13544

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

🎓Northeastern UniversityShenyang · China2026 · 1 papercurrent🎓Chongqing Technology and Business UniversityChongqing · China2019–2024 · 6 papers🎓Michigan Technological UniversityHoughton · United States2008–2012 · 6 papers🎓Qufu Normal UniversityQufu · China2022–2024 · 4 papers🎓Shandong UniversityJinan · China2007–2016 · 3 papers🎓Northeastern UniversityBoston · United States2025 · 2 papers🏢Ant GroupHangzhou · China2016–2017 · 2 papers🏢MicrosoftRedmond · United States2012–2015 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 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.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksComputer Vision and Pattern Recognition · 2 worksArtificial Intelligence · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 1 workReasoning · 1 workVision & language · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. DPN-LE: Dual Personality Neuron Localization and Editing for Large Language Models (2026)
    Neuron-editing approaches to steering the personality of large language models, such as NPTI, alter tens of thousands of MLP neurons per trait and harm general abilities.
  2. RATION: Entropy-Driven Task-Adaptive Visual Attention Allocation Framework for Multimodal Reasoning (2026)
    Multimodal LLMs often fail on visually demanding questions because they spread visual attention badly. In counting, attention can lock onto a few spots and miss objects. In OCR, it can drift over irrelevant regions instead of the text. The authors argue that earlier fixes, such as better alignment, chain-of-thought…

 Co-authors here

12 of 14 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.

Updated

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