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Bo Dai

Bo Dai has 2 papers in our library, in 2023–2025, most of them on Language models & pretraining, Reasoning; often with Chao Zhang, Daixuan Cheng, Furu Wei.

2 papers in our library · 2023–2025

OpenAlex · ORCID · h-index 10 · 26 works · 372 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 132 times in our library · ⭐ Paper Stars ranking: #7004

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

🎓Beihang UniversityBeijing · China2025 · 1 papercurrent🏛️Beijing Institute for General Artificial IntelligenceBeijing · China2025 · 1 papercurrent🎓Georgia Institute of TechnologyAtlanta · United States2025 · 1 papercurrent🏛️Chinese Academy of SciencesBeijing · China2016–2024 · 10 papers🎓University of Chinese Academy of SciencesBeijing · China2016–2024 · 10 papers🔬Shenyang Institute of AutomationShenyang · China2016–2024 · 9 papers🎓Beijing Institute of Petrochemical TechnologyBeijing · China2006–2019 · 9 papers🔬State Key Laboratory of RoboticsLiaoning2017–2024 · 8 papers

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 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20251 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. AdaPlanner: Adaptive Planning from Feedback with Language Models (2023 · 93 citations)
    LLM agents for sequential decision-making usually either act step by step without any plan or follow a fixed plan, adjusting only the current action when the environment responds.
  2. Reasoning with Exploration: An Entropy Perspective (2025 · 63 citations)
    RL training of LLMs with verifiable rewards tends to over-exploit. Models settle into narrow strategies, and reasoning gains level off. The authors ask whether token-level entropy, a classic exploration signal in RL, can identify exploratory reasoning. They analyse Qwen2.5-Base-7B on math problems and find that…

 Co-authors here

10 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 132 times (of the 149,439 papers whose bibliographies we read); 39 citing papers with a page here →.

Updated

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