Hao He
Hao He has 2 papers in our library, in 2021–2023, most of them on Language models & pretraining, Reasoning; often with Zhengliang Liu.
OpenAlex · ORCID · h-index 12 · 87 works · 1,375 citations OpenAlex, 2026-10-14
📄 2 works in our library · 🔗 Cited 155 times in our library · ⭐ Paper Stars ranking: #2176
Affiliations
🎓Emporia State UniversityEmporia ·
United States2023–2026 · 11 papers🎓Chengdu University of TechnologyChengdu ·
China2025–2026 · 3 papers🎓Northwestern Polytechnical UniversityXi'an ·
China2026 · 1 paper🎓The University of Texas Health Science Center at HoustonHouston ·
United States2026 · 1 paper🎓University of MissouriColumbia ·
United States2019–2024 · 14 papers🎓University of Electronic Science and Technology of ChinaChengdu ·
China2007–2021 · 10 papers🎓Central Academy of Fine ArtsBeijing ·
China2018–2024 · 8 papers🎓Shanghai Jiao Tong UniversityShanghai ·
China2019–2024 · 6 papers🎓University of FloridaGainesville ·
United States2012 · 4 papers🎓Texas A&M UniversityCollege Station ·
United States2013–2017 · 3 papers
Concepts, shelves and topics
📚 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
🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 1 workReasoning · 1 work
Works by year
2020s
20231 paperSummary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models20211 paperDiagnosing the First-Order Logical Reasoning Ability Through LogicNLI
Papers
- Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models (2023 · 938 citations)
This survey maps the early wave of research on ChatGPT (GPT-3.5 and GPT-4) after its December 2022 release. - Diagnosing the First-Order Logical Reasoning Ability Through LogicNLI (2021 · 86 citations)
Pretrained Transformers score well on many NLU benchmarks, but it is unclear whether they actually perform first-order logic (FOL) reasoning or exploit dataset artifacts and commonsense cues.
Co-authors here
Venues
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