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Jaewoo Kang

Jaewoo Kang has 5 papers in our library, in 2019–2023, most of them on Language models & pretraining, Question answering, Knowledge graphs & ontologies; often with Jinhyuk Lee, Sungdong Kim, Gangwoo Kim.

5 papers in our library · 2019–2023

OpenAlex · ORCID · Wikidata · h-index 50 · 298 works · 16,506 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 1,446 times in our library · 7 more in our library without a page yet · ⭐ Paper Stars ranking: #304

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

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

2010s

 Papers

The most cited first (OpenAlex and our library).

  1. BioBERT: a pre-trained biomedical language representation model for biomedical text mining (2019 · 8,311 citations)
    Biomedical literature grows faster than researchers can read it, so automatic text mining matters more each year.
  2. Can Language Models be Biomedical Knowledge Bases? (2021 · 127 citations)
    This work asks whether pre-trained language models can act as knowledge bases for expert biomedical facts, rather than the general trivia tested by LAMA.
  3. Learning Dense Representations of Phrases at Scale (2021 · 126 citations)
    DensePhrases tackles open-domain question answering as retrieval over a pre-built index of phrases. It does not run a reader model over retrieved documents at query time. Earlier phrase-retrieval systems (DenSPI, DenSPI + Sparc) relied on sparse vectors and still trailed retriever-reader pipelines. The authors ask…
  4. Look at the First Sentence: Position Bias in Question Answering (2020 · 102 citations)
    Extractive QA models usually output start and end indices of an answer span. The authors ask whether this design lets models exploit answer location instead of reading. They build deliberately skewed training sets from SQuAD in which every answer sits in the same sentence (mainly the first). When trained this way…
  5. Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language Models (2023 · 82 citations)
    Open-domain questions are often ambiguous: one query can admit several readings, each with its own answer.

All works

12 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them.

  1. Improving Medical Reasoning through Retrieval and Self-Reflection with Retrieval-Augmented Large Language Models · original ↗ · no summary yet · arXiv:2401.15269Minbyul Jeong et al.2024 · 164 citations
  2. Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks · original ↗ · no summary yet · arXiv:2404.00376Hyunjae Kim et al.2024 · 75 citations
  3. CompAct: Compressing Retrieved Documents Actively for Question Answering · original ↗ · no summary yet · Proceedings of the 2024 Conference on Empirical Methods in Natural Language…Chanwoong Yoon et al.2024 · 33 citations
  4. Fine-tuning CLIP Text Encoders with Two-step Paraphrasing · original ↗ · no summary yet · Findings of the Association for Computational Linguistics: EACL 2024Hyunjae Kim et al.2024 · 3 citations
  5. ToxReason: A Benchmark for Mechanistic Chemical Toxicity Reasoning via Adverse Outcome Pathway · original ↗ · no summary yet · Findings of the Association for Computational Linguistics: ACL 2026Jueon Park et al.2026
  6. CLAG: Adaptive Memory Organization via Agent-Driven Clustering for Small Language Model Agents · original ↗ · no summary yet · Findings of the Association for Computational Linguistics: ACL 2026Taeyun Roh et al.2026
  7. Lack of Fluency is Hurting Your Translation Model · original ↗ · no summary yet · arXiv:2205.11826Jaehyo Yoo, Jaewoo Kang2022

 Co-authors here

7 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 1,446 times (of the 141,840 papers whose bibliographies we read); 88 citing papers with a page here →.

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