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Haonan Wang

Haonan Wang has 2 papers in our library, in 2026, most of them on Language models & pretraining, Efficient models & compression; often with Chao Du, Jiafeng Guo, Jiaying Wu.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 15 · 40 works · 565 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 6 times in our library · ⭐ Paper Stars ranking: #10397

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

🎓Wuhan University of TechnologyWuhan · China2019–2026 · 10 paperscurrent🎓Northeastern UniversityShenyang · China2019–2023 · 7 papers🎓University of Science and Technology BeijingBeijing · China2019–2020 · 5 papers🎓Qingdao UniversityQingdao · China2024–2025 · 3 papers🏛️Chinese Academy of SciencesBeijing · China2019 · 3 papers🔬Shenyang Institute of AutomationShenyang · China2019 · 3 papers🔬State Key Laboratory Fluid Power and Mechatronic SystemsHangzhou · China2024 · 2 papers🎓Zhejiang UniversityHangzhou · China2024 · 2 papers🎓Chongqing UniversityChongqing · China2021 · 2 papers🔬State Key Laboratory of RoboticsLiaoning2019 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 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 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksSocial Sciences · 1 workSociology and Political Science · 1 work

🧭 Topics 2Research subjects and languages the work is about.Efficient models & compression · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification (2026 · 5 citations)
    Speculative decoding (SD) speeds up LLM inference without changing outputs. However, leading SD drafters such as EAGLE are trained on short sequences (about 2k–4k tokens) and break down when contexts get very long. The authors identify three causes:
  2. Beyond the Crowd: LLM-Augmented Community Notes for Governing Health Misinformation (2026 · 1 citation)
    Community Notes on X lets volunteers attach context to misleading posts, but the process is slow. The authors studied 30.8K English health-related notes and found that corrections usually arrive after public attention has peaked. Most notes never get enough votes to be shown at all. To speed this up, they propose…

 Co-authors here

6 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 6 times (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated

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