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Clayton Washington

Clayton Washington has 2 papers in our library, in 2022, most of them on Language models & pretraining; often with Yu Su, Bernal Jimenez Gutierrez, Huan Sun.

2 papers in our library · 2022

OpenAlex · ORCID · h-index 2 · 6 works · 482 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 208 times in our library · ⭐ Paper Stars ranking: #2675

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

🎓Emory UniversityAtlanta · United States2025–2026 · 2 paperscurrent🎓Georgia Institute of TechnologyAtlanta · United States2025–2026 · 2 paperscurrent🎓The Ohio State UniversityColumbus · United States2022–2023 · 2 papers

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.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksControl and Systems Engineering · 1 workEngineering · 1 workArts and Humanities · 1 workBiochemistry, Genetics and Molecular Biology · 1 workLanguage and Linguistics · 1 workMolecular Biology · 1 work

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

 Works by year

2020s

20222 papersClayton Washington's papers of 2022

 Papers

The most cited first (OpenAlex and our library).

  1. LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models (2022 · 564 citations)
    Language-driven embodied agents usually need many annotated instruction–trajectory pairs for every task, which makes them expensive to build and slow to extend.
  2. Thinking about GPT-3 In-Context Learning for Biomedical IE? Think Again (2022 · 179 citations)
    Annotating biomedical text for information extraction is expensive, so GPT-3's ability to learn from a few prompt examples looks attractive.

 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 208 times (of the 141,840 papers whose bibliographies we read); 22 citing papers with a page here →.

Updated

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