Papers by Jeonghyun Kang
Generation-Based and Emotion-Reflected Memory Update: Creating the KEEM Dataset for Better Long-Term Conversation (2025.coling-main)
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| Challenge: | KEEM is a dynamically generated dataset designed to enhance memory updates in long-term conversational systems. |
| Approach: | They propose a dataset that keeps emotional and essential memories and generates integrative memories that incorporate emotional context and causal relationships. |
| Outcome: | The Keep Emotional and Essential Memory (KEEM) dataset enhances memory updates in long-term conversational systems. |
Can Large Language Models Differentiate Harmful from Argumentative Essays? Steps Toward Ethical Essay Scoring (2025.coling-main)
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| Challenge: | Existing automated essay scoring systems overlook ethical and moral aspects of content, erroneously assigning high scores to essays that propagate harmful opinions. |
| Approach: | They introduce a Harmful Essay Detection benchmark to test the effectiveness of various Large Language Models (LLMs) they find that current AES systems overlook ethically and morally problematic elements in essays . |
| Outcome: | The proposed benchmark compared LLMs and AES models to identify and score harmful essays. |