🧑‍🔬 Joseph Chee Chang

🏛️ Affiliations

🔬Allen Institute for Artificial IntelligenceSeattle · United States2022–2026 · 33 paperscurrent🎓University of WashingtonSeattle · United States2026 · 2 paperscurrent🎓University of MinnesotaMinneapolis · United States2026 · 1 papercurrent🎓Carnegie Mellon UniversityPittsburgh · United States2016–2021 · 11 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.

🧭 Fields, topics and concepts

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

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs (2024 · 62 citations)
   Large language models often fail researchers who need to digest scientific literature. They invent references, rely on outdated pre-training knowledge, and seldom show the sources behind their claims. OpenScholar addresses this with a fully open retrieval-augmented system built on OpenScholar-DataStore (OSDS), an…
2. SciArena: An Open Evaluation Platform for Non-Verifiable Scientific Literature-Grounded Tasks (2025 · 11 citations)
   Judging how well foundation models answer open-ended research questions that rely on scientific papers is hard.

All works

6 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. OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMsarXiv:2411.14199Akari Asai, Jacqueline He, Rulin Shao, et al.2024 · 62 citations
2. Synthesizing scientific literature with retrieval-augmented language models ↗Nature · no summary yetAkari Asai et al.2026 · 42 citations
3. SciArena: An Open Evaluation Platform for Non-Verifiable Scientific Literature-Grounded TasksConference on Neural Information Processing Systems (NeurIPS)Yilun Zhao, Kaiyan Zhang, Tiansheng Hu, et al.2025 · 11 citations
4. Contextualized Evaluations: Judging Language Model Responses to Underspecified Queries ↗Transactions of the Association for Computational Linguistics · no summary yetChaitanya Malaviya et al.2025 · 8 citations
5. Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetNishant Balepur et al.2026 · 2 citations
6. DRACULA: Hunting for the Actions Users Want Deep Research Agents to Execute ↗arXiv (Cornell University) · no summary yetNishant Balepur et al.2026 · 1 citation

🤝 Co-authors here

12 of 19 co-authors with a page, the most papers together first.

• Matt Latzke ×2
• Akari Asai
• Amanpreet Singh
• David Wadden
• Jesse Dodge
• Jonathan Bragg
• Kaiyan Zhang
• Kyle Lo
• Luca Soldaini
• Mike D'arcy
• Ronan Le Bras
• Rulin Shao

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Conference on Neural Information Processing Systems (NeurIPS): NeurIPS 2025
• Nature
• Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
• Transactions of the Association for Computational Linguistics

🔗 Cited by

Papers of our library cite their works 83 times (of the 149,439 papers whose bibliographies we read); 21 citing papers with a page here →.

Updated 2 November 2026

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