🧑‍🔬 Jinsung Yoon

🏛️ Affiliations

🏢GoogleMountain View · United States2020–2026 · 49 paperscurrent🎓Pohang University of Science and TechnologyPohang · South Korea2025–2026 · 2 paperscurrent🎓University of California, Los AngelesLos Angeles · United States2004–2022 · 46 papers🎓University of BolognaBologna · Italy2018–2022 · 8 papers🎓University of California SystemOakland · United States2016–2021 · 3 papers🏢Google DeepMindLondon · United Kingdom2024 · 2 papers🎓Korea Aerospace UniversityGoyang-si · South Korea2023 · 2 papers🎓Soongsil UniversitySeoul · South Korea2003–2004 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 more institutions 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.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning (2025 · 303 citations)
   Large language models often need outside, current knowledge, but simply prompting them to use a search engine works poorly because they were never trained to interact with one.
2. BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval (2024 · 70 citations)
   Standard retrieval benchmarks such as BEIR and MTEB mostly test search-engine-style questions. In these, relevant documents share many words or meanings with the query. Many real needs are harder. A programmer may need documentation for a function that is never named in the question, or a student may need a problem…

All works

3 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. Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement LearningarXiv:2503.09516Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.2025 · 303 citations
2. BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive RetrievalarXiv:2407.12883Hongjin Su, Howard Yen, Mengzhou Xia, et al.2024 · 70 citations
3. DocLens: A Tool-Augmented Multi-Agent Framework for Long Visual Document UnderstandingProceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · original ↗ · no summary yetDawei Zhu et al.2026 · 2 citations

🤝 Co-authors here

9 co-authors with a page, the most papers together first.

• Bowen Jin
• Dong Wang
• Hamed Zamani
• Hongjin Su
• Howard Yen
• Jiawei Han
• Mengzhou Xia
• Niklas Muennighoff
• Weijia Shi

Venues

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

• Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

🔗 Cited by

Papers of our library cite their works 356 times (of the 141,840 papers whose bibliographies we read); 7 citing papers with a page here →.

Updated 24 October 2026

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/jinsung-yoon/