Sunghwan Kim
Orcid: 0009-0003-9514-812XAffiliations:
- Yonsei University, Department of Artificial Intelligence, Seoul, South Korea
According to our database1,
Sunghwan Kim authored at least 15 papers
between 2024 and 2026.
Collaborative distances:
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Bibliography
2026
On Training Large Language Models for Long-Horizon Tasks: An Empirical Study of Horizon Length.
CoRR, May, 2026
Success and failure of human-AI collaboration in clinical reasoning: An experimental study on challenging real-world cases.
Int. J. Medical Informatics, 2026
Proceedings of the ACM Web Conference 2026, 2026
2025
Embodied Agents Meet Personalization: Exploring Memory Utilization for Personalized Assistance.
CoRR, May, 2025
Towards Personalized Conversational Sales Agents : Contextual User Profiling for Strategic Action.
CoRR, April, 2025
Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
ToolHaystack: Stress-Testing Tool-Augmented Language Models in Realistic Long-Term Interactions.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025
LLM Meets Scene Graph: Can Large Language Models Understand and Generate Scene Graphs? A Benchmark and Empirical Study.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
2024
Stop Playing the Guessing Game! Target-free User Simulation for Evaluating Conversational Recommender Systems.
CoRR, 2024
Cactus: Towards Psychological Counseling Conversations using Cognitive Behavioral Theory.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Can Large Language Models be Good Emotional Supporter? Mitigating Preference Bias on Emotional Support Conversation.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024