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Chengkai Huang

Chengkai Huang has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning, Information retrieval & search; often with Julian McAuley, Lina Yao, Jingbo Shang.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 4 · 30 works · 67 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 5 times in our library · ⭐ Paper Stars ranking: #10536

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

🎓UNSW SydneySydney · Australia2023–2026 · 26 paperscurrent🎓Macquarie UniversitySydney · Australia2025–2026 · 12 paperscurrent

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 · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 4Research subjects and languages the work is about.Information retrieval & search · 1 workLanguage models & pretraining · 1 workReasoning · 1 workVision & language · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Embedding-Informed Adaptive Retrieval-Augmented Generation of Large Language Models (2025 · 5 citations)
    Retrieval-augmented LLMs do not always benefit from external documents. When a model already knows the answer, retrieval adds cost and latency and can even hurt quality. Adaptive RAG (ARAG) tries to retrieve only when needed. Earlier ARAG methods either count entity frequencies in the pre-training corpus, which is…
  2. SceneAlign: Aligning Multimodal Reasoning to Scene Graphs in Complex Visual Scenes (2026)
    Multimodal LLMs often produce rationales that sound convincing but are not tied to what the image actually shows.

 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.

 Cited by

Papers of our library cite their works 5 times (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated

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