Papers by Sejoon Kim

1 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.

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