Papers by Hyunkuk Lim

2 papers
REZE: Representation Regularization for Domain-adaptive Text Embedding Pre-finetuning (2026.acl-long)

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Challenge: Recent text embedding models often introduce task-induced bias alongside domain knowledge, leading to performance degradation.
Approach: They propose a representation regularization framework that explicitly controls representation shift during embedding pre-finetuning.
Outcome: The proposed framework outperforms standard pre-finetuning and isotropy-oriented post-hoc regularization in most settings.
TelME: Teacher-leading Multimodal Fusion Network for Emotion Recognition in Conversation (2024.naacl-long)

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Challenge: Emotion Recognition in Conversation (ERC) aims to identify emotions expressed by participants at each turn within a conversation.
Approach: They propose a Teacher-leading Multimodal fusion network for ERC that integrates cross-modal knowledge distillation to transfer information from a lan- guage model acting as the teacher to non- verbal students.
Outcome: The proposed model achieves state-of-the-art in a multi-speaker conversation dataset for ERC.

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