Papers by Yeonsoo Lee
HaRiM+: Evaluating Summary Quality with Hallucination Risk (2022.aacl-main)
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| Challenge: | Existing summarization models are limited in measuring the factual inconsistency of generated summaries. |
| Approach: | They propose a decoder overconfidence-regularizing objective as a hallucination risk measurement to better estimate the quality of generated summaries. |
| Outcome: | The proposed metric is reference-free and requires no training or modules . it records state-of-the-art correlation to human judgment on three sets of summary-quality annotations. |
Persona Expansion with Commonsense Knowledge for Diverse and Consistent Response Generation (2023.eacl-main)
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Donghyun Kim, Youbin Ahn, Wongyu Kim, Chanhee Lee, Kyungchan Lee, Kyong-Ho Lee, Jeonguk Kim, Donghoon Shin, Yeonsoo Lee
| Challenge: | Existing researches have focused on generating diverse and consistent responses based on personal traits. |
| Approach: | They propose a consistent persona expansion framework that improves not only the diversity but also the consistency of persona-based responses. |
| Outcome: | The proposed framework improves not only the diversity but also the consistency of persona-based responses on the Persona-Chat dataset. |
Concept-based Persona Expansion for Improving Diversity of Persona-Grounded Dialogue (2023.eacl-main)
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| Challenge: | Existing approaches to improve the quality of persona-grounded dialogues are limited to a few informative words. |
| Approach: | They propose a concept-based persona expansion framework that takes the original persona as input and generates expanded personas that contain conceptually rich content. |
| Outcome: | The proposed framework improves the quality of persona-grounded dialogue responses in diversity and richness. |
Align-to-Distill: Trainable Attention Alignment for Knowledge Distillation in Neural Machine Translation (2024.lrec-main)
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| Challenge: | Existing knowledge distillation approaches to NMT often rely on heuristics when deciding which teacher layers to distill from. |
| Approach: | They propose an approach to align student attention heads with their teacher counterparts by heuristics to solve a feature mapping problem. |
| Outcome: | The proposed strategy shows gains of +3.61 and +0.63 BLEU points for WMT-2022 DeDsb and WMT-2014 EnDe compared to baselines. |
Do LLMs Have Distinct and Consistent Personality? TRAIT: Personality Testset designed for LLMs with Psychometrics (2025.findings-naacl)
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Seungbeen Lee, Seungwon Lim, Seungju Han, Giyeong Oh, Hyungjoo Chae, Jiwan Chung, Minju Kim, Beong-woo Kwak, Yeonsoo Lee, Dongha Lee, Jinyoung Yeo, Youngjae Yu
| Challenge: | Recent advances in Large Language Models (LLMs) have led to their adaptation as conversational agents. |
| Approach: | They propose a new benchmark that uses 8K multi-choice questions to assess the personality of Large Language Models. |
| Outcome: | The proposed personality test outperforms existing personality tests for LLMs in reliability and validity. |