activity
20232025
most citedRefineBench: Evaluating Refinement Capability of Language Models via Checklists

1 citations · 2 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2025★ 1 cited

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…

cs.CV2025

MultiVerse: A Multi-Turn Conversation Benchmark for Evaluating Large Vision and Language Models

Young-Jun Lee, Byung-Kwan Lee, Jianshu Zhang +9

Vision-and-Language Models (VLMs) have shown impressive capabilities on single-turn benchmarks, yet real-world applications often demand more intricate multi-turn dialogues. Existi…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024★ 1 cited

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…

cs.CV2024

Intriguing Properties of Large Language and Vision Models

Young-Jun Lee, Byungsoo Ko, Han-Gyu Kim +2

Recently, large language and vision models (LLVMs) have received significant attention and development efforts due to their remarkable generalization performance across a wide rang…

cs.CL2024

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…

cs.CL2024

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…

cs.CV2023

Large Language Models can Share Images, Too!

Young-Jun Lee, Dokyong Lee, Joo Won Sung +2

This paper explores the image-sharing capability of Large Language Models (LLMs), such as GPT-4 and LLaMA 2, in a zero-shot setting. To facilitate a comprehensive evaluation of LLM…