Bingquan Liu
Bingquan Liu has 2 papers in our library, in 2010–2026, most of them on Reasoning; often with Chengjie Sun, Yong Cheng, Yue Wang.
OpenAlex · ORCID · Wikidata · h-index 20 · 150 works · 1,332 citations OpenAlex, 2026-10-14
📄 2 works in our library · 🔗 Cited 32 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #9914
Affiliations
Fields, topics and concepts
📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksBiochemistry, Genetics and Molecular Biology · 1 workMolecular Biology · 1 workComputational Theory and Mathematics · 1 work
🧭 Topics 1Research subjects and languages the work is about.Reasoning · 1 work
💡 Concepts 1Key ideas and methods explained on our concept pages.Minimum description length · 1 work
Works by year
2020s
2010s
Papers
- Learning to Detect Hedges and their Scope Using CRF (2010 · 10 citations)
The paper describes a CoNLL-2010 shared task entry that identifies speculative language (hedges) in biomedical writing. - Time-for-Accuracy: Formalizing Chain-of-Thought as an Expansion of Logical Depth (2026)
Chain-of-thought prompting often helps LLMs on multi-step problems, but it is unclear what extra computation a longer trace actually provides.
All works
- Neural Response Generation via GAN with an Approximate Embedding Layer ↗Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing · no summary yetZhen Xu et al.2017 · 118 citations
- Learning to Detect Hedges and their Scope Using CRFConference on Computational Natural Language Learning (CoNLL)Qi Zhao, Chengjie Sun, Bingquan Liu, et al.2010 · 10 citations
- Time-for-Accuracy: Formalizing Chain-of-Thought as an Expansion of Logical DepthFindings of the Association for Computational LinguisticsYue Wang, Zhi Zhang, Wang Xi, et al.2026
Co-authors here
Venues
- Conference on Computational Natural Language Learning (CoNLL): CoNLL 2010
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
- Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
Cited by
Updated
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