🧑‍🔬 Heuiseok Lim

🏛️ Affiliations

🎓Korea UniversitySeoul · South Korea1994–2026 · 237 papersEducation 1994–1997 · Ph.D, Computer ScienceEmploymentcurrent🎓Korea UniversityTokyo · Japan2015–2026 · 57 paperscurrent🎓Hanshin UniversityOsan · South Korea2005–2008 · 6 papers🏢UpStageYongin-si · South Korea2023–2024 · 2 papers🎓Chodang UniversityMuan · South Korea2002 · 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.

🧭 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. PEEP-Talk: A Situational Dialogue-based Chatbot for English Education (2023 · 9 citations)
   Learners of English as a foreign language rarely get to practise realistic conversation. Existing tutoring chatbots tend to be rule-based, cope poorly with off-topic input, and give little feedback. PEEP-Talk addresses this with three parts:
2. HiKEY: Hierarchical Multimodal Retrieval for Open-Domain Document Question Answering (2026)
   The paper tackles retrieval-augmented question answering over large collections of long, multi-page PDFs. Such documents mix prose with tables and figures, and systems often fail in two ways: they pick the wrong document from thousands of candidates, or they return evidence fragments that stay disconnected. Standard…
3. I Don't Need Solution. I Need Emotional Support : Empathetic LLMs based on Emotional Validation (2026)
   LLMs used as emotional-support chatbots tend to jump straight to advice. They repeat stock phrases and ignore how the help-seeker's feelings evolve over a dialogue. In a pilot study on ESConv, crowd workers judged most Mistral and GPT-4o replies as not comforting. To fix this, the authors propose EVA, a framework…
4. NeedleChain: Measuring Intact Context Comprehension Capability of Large Language Models (2026)
   Long-context benchmarks for LLMs usually mix a small amount of query-relevant evidence with a lot of filler, as in the needle-in-a-haystack (NIAH) setup.

All works

16 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

1. I Know What You Asked: Graph Path Learning using AMR for Commonsense Reasoning ↗Proceedings of the 28th International Conference on Computational Linguistics · no summary yetJungwoo Lim et al.2020 · 48 citations
2. Improving Formality-Sensitive Machine Translation Using Data-Centric Approaches and Prompt Engineering ↗Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023) · no summary yetSeungjun Lee et al.2023 · 11 citations
3. PEEP-Talk: A Situational Dialogue-based Chatbot for English EducationAnnual Meeting of the Association for Computational Linguistics (ACL)Seungjun Lee, Yoonna Jang, Chanjun Park, et al.2023 · 9 citations
4. Explainable CED: A Dataset for Explainable Critical Error Detection in Machine Translation ↗Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop) · no summary yetDahyun Jung et al.2024 · 5 citations
5. KU X Upstage's Submission for the WMT22 Quality Estimation: Critical Error Detection Shared Task ↗Proceedings of the Seventh Conference on Machine Translation (WMT) · no summary yetSugyeong Eo et al.2022 · 5 citations
6. Debate Only When Necessary: Adaptive Multiagent Collaboration for Efficient LLM Reasoning ↗arXiv:2504.05047 · no summary yetSugyeong Eo et al.2025 · 4 citations
7. Towards Precise Localization of Critical Errors in Machine Translation ↗Findings of the Association for Computational Linguistics: ACL 2024 · no summary yetDahyun Jung, Sugyeong Eo, Heuiseok Lim2024 · 1 citation
8. Data-Driven Approach for Formality-Sensitive Machine Translation: Language-Specific Handling and Synthetic Data Generation ↗arXiv:2306.14514 · no summary yetSeugnjun Lee et al.2023 · 1 citation
9. QUAK: A Synthetic Quality Estimation Dataset for Korean-English Neural Machine Translation ↗Proceedings of the 29th International Conference on Computational Linguistics · no summary yetSugyeong Eo et al.2022 · 1 citation
10. HiKEY: Hierarchical Multimodal Retrieval for Open-Domain Document Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Joongmin Shin, Gyuho Shim, Jeongbae Park, et al.2026
11. I Don't Need Solution. I Need Emotional Support : Empathetic LLMs based on Emotional ValidationFindings of the Association for Computational LinguisticsSuhyune Son, Jungwoo Lim, Myunghoon Kang, et al.2026
12. NeedleChain: Measuring Intact Context Comprehension Capability of Large Language ModelsFindings of the Association for Computational LinguisticsHyeonseok Moon, Heuiseok Lim2026
13. Reliable Evaluation Protocol for Low-Precision Retrieval ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) · no summary yetKisu Yang et al.2026
14. Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetJeongho Yoon et al.2026
15. KoLEG: On-the-Fly Korean Legal Knowledge Editing with Continuous Retrieval ↗Findings of the Association for Computational Linguistics: EMNLP 2025 · no summary yetJaehyung Seo et al.2025
16. Detecting Critical Errors Considering Cross-Cultural Factors in English-Korean Translation ↗Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) · no summary yetSugyeong Eo et al.2024

🤝 Co-authors here

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

• Hyeonseok Moon ×2
• Jaehyung Seo ×2
• Chanjun Park

Venues

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

• Annual Meeting of the Association for Computational Linguistics (ACL) ×4: ACL 2026, ACL 2023
• Findings of the Association for Computational Linguistics ×2: Findings of the Association for Computational Linguistics 2026 ×2
• Proceedings of the 29th International Conference on Computational Linguistics ×2
• Findings of the Association for Computational Linguistics: ACL 2024
• Findings of the Association for Computational Linguistics: EMNLP 2025
• Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop)
• Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
• Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)
• Proceedings of the Seventh Conference on Machine Translation (WMT)

🔗 Cited by

Papers of our library cite their works 47 times (of the 149,439 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated 1 November 2026

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