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Lionel Wong

Lionel Wong has 2 papers in our library, in 2023–2026, most of them on Language models & pretraining, Evaluation & benchmarks; often with Benjamin Lipkin, Joshua B. Tenenbaum, Monica Agrawal.

2 papers in our library · 2023–2026

OpenAlex · h-index 5 · 22 works · 333 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 55 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #9223

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

🎓Stanford UniversityStanford · United States2021–2026 · 26 paperscurrent🎓Massachusetts Institute of TechnologyCambridge · United States2022–2026 · 25 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 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).Artificial Intelligence · 1 workArts and Humanities · 1 workComputer Science · 1 workLanguage and Linguistics · 1 workGeneral Health Professions · 1 workHealth Informatics · 1 workHealth Information Management · 1 workHealth Professions · 1 workMedicine · 1 work

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

 Works by year

2020s

20261 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Evaluating statistical language models as pragmatic reasoners (2023 · 18 citations)
    Vague words such as "strong" have no fixed cutoff, so their interpretation depends on context. Classic accounts compute this with recursive Bayesian models such as Rational Speech Acts (RSA). Lipkin and colleagues test whether a large language model can do this work without explicit computation. They describe a…
  2. MedRedFlag: Investigating how LLMs Redirect Misconceptions in Real-World Health Communication (2026)
    Patients often build their health questions on mistaken beliefs, such as trusting an implausible wearable reading or assuming a rare diagnosis.

All works

4 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Evaluating Language Models for Mathematics through Interactions ↗arXiv:2306.01694 · no summary yetKatherine M. Collins et al.2023 · 40 citations
  2. Evaluating statistical language models as pragmatic reasonersarXiv:2305.01020Benjamin Lipkin, Lionel Wong, Gabriel Grand, et al.2023 · 18 citations
  3. On Benchmarking Human-Like Intelligence in Machines ↗arXiv:2502.20502 · no summary yetLance Ying et al.2025 · 7 citations
  4. MedRedFlag: Investigating how LLMs Redirect Misconceptions in Real-World Health CommunicationFindings of the Association for Computational LinguisticsSraavya Sambara, Yuan Pu, Ayman Ali, et al.2026

 Co-authors here

3 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 55 times (of the 149,439 papers whose bibliographies we read); 21 citing papers with a page here →.

Updated

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