Papers by Suhyune Son
EASE: Entity-Aware Sub-table Generation for Real-world Multi-table QA (2026.acl-long)
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Myunghoon Kang, Dahyun Jung, Suhyune Son, Seonmin Koo, Changwoo Chun, Daniel Rim, Haeyoung Kwon, Yuna Hur, Heuiseok Lim
| Challenge: | Table-based question answering (table QA) is a powerful tool for analyzing large language models. |
| Approach: | They propose to use noisy multi-table sets to generate sub-tables for table-based question answering. |
| Outcome: | The proposed framework efficiently filters out irrelevant information while incorporating pertinent table values. |
I Don’t Need Solution. I Need Emotional Support : Empathetic LLMs based on Emotional Validation (2026.findings-acl)
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| Challenge: | Existing large language models (LLMs) struggle to generate emotional support response, despite observing and reflecting on the help-seeker’s situation . Empathy drives the formation of constructive interpersonal and supportive relationships, including counseling for mental health care . |
| Approach: | They propose to use a two-stage training process to enhance empathetic response generation through empathy acquisition and emotional validation alignment. |
| Outcome: | The proposed method significantly improves empathetic response generation, achieving superior performance in both automatic and human evaluations. |
Post-hoc Utterance Refining Method by Entity Mining for Faithful Knowledge Grounded Conversations (2023.emnlp-main)
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Yoonna Jang, Suhyune Son, Jeongwoo Lee, Junyoung Son, Yuna Hur, Jungwoo Lim, Hyeonseok Moon, Kisu Yang, Heuiseok Lim
| Challenge: | Despite advances in language generation, models suffer from hallucinations that are either untrue or unfaithful to a given source. |
| Approach: | They propose a method to refine hallucinated utterances based on source knowledge . REM implicitly uses key entities in the knowledge to refine the utterant . |
| Outcome: | The proposed method reduces entity hallucination in the generated utterance and improves the quality of the model. |