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Yunghwei Lai

Yunghwei Lai has 2 papers in our library, in 2024–2026, most of them on Language models & pretraining; often with Ante Wang, Bosi Wen, Jinfeng Zhou.

2 papers in our library · 2024–2026

OpenAlex · h-index 2 · 3 works · 14 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 54 times in our library · ⭐ Paper Stars ranking: #7437

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

🎓Beijing Institute of TechnologyBeijing · China2024 · 2 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 9The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksPsychology · 1 workArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workDevelopmental and Educational Psychology · 1 workSafety Research · 1 workSocial Sciences · 1 work

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

 Works by year

2020s

20261 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. ToMBench: Benchmarking Theory of Mind in Large Language Models (2024 · 62 citations)
    Whether large language models possess a theory of mind (ToM) is disputed. Earlier tests gave conflicting results, covered only narrow aspects such as beliefs or emotions, relied on costly manual scoring of open answers, and often reused classic psychology materials that LLMs may have seen during training. ToMBench…
  2. Beyond “I Don't Know”: Evaluating LLM Self-Awareness in Discriminating Data and Model Uncertainty (2026 · 3 citations)
    Most work on LLM abstention treats every refusal the same way. This paper argues that a reliable model also needs to know why it is unsure. It separates two sources of uncertainty. Data uncertainty means the question is ambiguous or missing information, which calls for asking the user to clarify. Model uncertainty…

 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 54 times (of the 149,439 papers whose bibliographies we read); 13 citing papers with a page here →.

Updated

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