Papers by Hyun-Je Song

2 papers
Selective Span-Level Unlearning for Large Language Models (2026.acl-short)

Copied to clipboard

Challenge: Existing selective methods that focus on identifying token-level or span-level unlearning targets are misaligning unlearning objectives with the model’s internal behavior.
Approach: They propose a selective method that uses model-intrinsic information to identify token-level or span-level unlearning targets within a text rather than entire sequences.
Outcome: The proposed method achieves comparable unlearning performance while significantly better preserving retained knowledge.
Korean Morphological Analysis with Tied Sequence-to-Sequence Multi-Task Model (D19-1)

Copied to clipboard

Challenge: Korean morphological analysis is a sequence of morpheme processing and POS tagging.
Approach: They propose a tied sequence-to-sequence multi-task model for training the two tasks simultaneously without any explicit regularization.
Outcome: The proposed model achieves state-of-the-art performance without any explicit regularization.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations