1 citations · 2 across the 8 of their papers we have counts for
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RefineBench: Evaluating Refinement Capability of Language Models via Checklists
Young-Jun Lee, Seungone Kim, Byung-Kwan Lee +6
Can language models (LMs) self-refine their own responses? This question is increasingly relevant as a wide range of real-world user interactions involve refinement requests. Howev…
LANGALIGN: Enhancing Non-English Language Models via Cross-Lingual Embedding Alignment
Jong Myoung Kim, Young-Jun Lee, Ho-Jin Choi +1
While Large Language Models have gained attention, many service developers still rely on embedding-based models due to practical constraints. In such cases, the quality of fine-tun…
PAD: Towards Efficient Data Generation for Transfer Learning Using Phrase Alignment
Jong Myoung Kim, Young-Jun_Lee, Ho-Jin Choi +1
Transfer learning leverages the abundance of English data to address the scarcity of resources in modeling non-English languages, such as Korean. In this study, we explore the pote…
Thanos: Enhancing Conversational Agents with Skill-of-Mind-Infused Large Language Model
Young-Jun Lee, Dokyong Lee, Junyoung Youn +2
To increase social bonding with interlocutors, humans naturally acquire the ability to respond appropriately in a given situation by considering which conversational skill is most…
Does Incomplete Syntax Influence Korean Language Model? Focusing on Word Order and Case Markers
Jong Myoung Kim, Young-Jun Lee, Yong-jin Han +2
Syntactic elements, such as word order and case markers, are fundamental in natural language processing. Recent studies show that syntactic information boosts language model perfor…
Stark: Social Long-Term Multi-Modal Conversation with Persona Commonsense Knowledge
Young-Jun Lee, Dokyong Lee, Junyoung Youn +4
Humans share a wide variety of images related to their personal experiences within conversations via instant messaging tools. However, existing works focus on (1) image-sharing beh…