From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed.

Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 7Arts and Humanities · 2 works Computer Science · 2 works Artificial Intelligence · 2 works Language and Linguistics · 2 works Psychology · 1 work Computer Vision and Pattern Recognition · 1 work Developmental and Educational Psychology · 1 work

🧭 Topics 1Dialogue systems · 1 work

Works by year

2020s

20231 paper 20221 paper

Papers

The most cited first (OpenAlex and our library).

How FaR Are Large Language Models From Agents with Theory-of-Mind? (2023 · 40 citations)
Theory-of-Mind (ToM) benchmarks for large language models, such as ToMi, usually ask directly about a character's beliefs.
Reflect, Not Reflex: Inference-Based Common Ground Improves Dialogue Response Quality (2022 · 34 citations)
Dialogue response generation (RG) models tend to produce bland, generic replies. The authors argue this happens because the models answer "reflexively": they map dialogue history straight to a response and skip the step people take of building common ground (CG), meaning the shared knowledge and beliefs between…

All works

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

Representing Numbers in NLP: a Survey and a Vision ↗Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetAvijit Thawani et al.2021 · 139 citations
Sparsity and Noise: Where Knowledge Graph Embeddings Fall Short ↗Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing · no summary yetJay Pujara, Eriq Augustine, Lise Getoor2017 · 132 citations
Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER ↗Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetDong-Ho Lee et al.2022 · 106 citations
Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources ↗Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · no summary yetNinareh Mehrabi et al.2021 · 65 citations
Self-Discover: Large Language Models Self-Compose Reasoning Structures ↗arXiv:2402.03620 · no summary yetPei Zhou et al.2024 · 61 citations
How FaR Are Large Language Models From Agents with Theory-of-Mind?arXiv:2310.03051Pei Zhou, Aman Madaan, Srividya Pranavi Potharaju, et al.2023 · 40 citations
Reflect, Not Reflex: Inference-Based Common Ground Improves Dialogue Response QualityConference on Empirical Methods in Natural Language Processing (EMNLP)Pei Zhou, Hyundong Cho, Pegah Jandaghi, et al.2022 · 34 citations

Co-authors here

11 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.

Conference on Empirical Methods in Natural Language Processing (EMNLP) ×3: EMNLP 2022
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Cited by

Papers of our library cite their works 247 times (of the 149,439 papers whose bibliographies we read); 29 citing papers with a page here →.

Updated 30 October 2026

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🧑‍🔬 Jay Pujara

🏛️ Affiliations

🧭 Fields, topics and concepts

📅 Works by year

2020s

📄 Papers

All works

🤝 Co-authors here

Venues

🔗 Cited by

Jay Pujara

Affiliations

Fields, topics and concepts

Works by year

Papers

Co-authors here

Cited by