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Haosen Wang

Haosen Wang has 2 papers in our library, in 2026, most of them on Language models & pretraining, Question answering, Reasoning; often with Can Xu, Dawei Yin, Jiayi Wu.

2 papers in our library · 2026

OpenAlex · h-index 0 · 4 works · 0 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #13593

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

🎓Carnegie Mellon UniversityPittsburgh · United States2026 · 1 papercurrent🎓Tianjin UniversityTianjin · 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).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 4Research subjects and languages the work is about.Language models & pretraining · 1 workQuestion answering · 1 workReasoning · 1 workVision & language · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Adversarial Yet Cooperative: Multi-Perspective Reasoning in Retrieved-Augmented Language Models (2026)
    Most agentic RAG systems rely on one model that both searches and reasons. When retrieved documents are incomplete or contradictory, that single viewpoint can reinforce its own mistakes. Training on final-answer rewards also cannot tell sound reasoning from a lucky guess. The authors propose ARR (Adversarial…
  2. Flow-Based Page Unique Semantic Mapping Architecture for Document Visual Question Answering (2026)
    The paper targets multi-page Document Visual Question Answering (DocVQA). OCR-free generative models still often pick the wrong evidence page when several pages look semantically alike, because they rank pages by coarse question–page similarity. The authors argue formally, through three propositions, that for a given…

 Co-authors here

9 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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