Jaechan Lee — accepted AI-conference papers

2025

MUSE: Machine Unlearning Six-Way Evaluation for Language Models

Weijia Shi, Jaechan Lee, Yangsibo Huang, Sadhika Malladi, Jieyu Zhao, Ari Holtzman +4

ICLR 2025poster

Language models (LMs) are trained on vast amounts of text data, which may include private and copyrighted content. Data owners may request the removal of their data from a trained model due to privacy or copyright concerns. However, exactly unlearning only these datapoints (i.e., retraining with the…

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2023

That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context?

Jaechan Lee, Alisa Liu, Orevaoghene Ahia, Hila Gonen, Noah A. Smith

EMNLP 2023long findings

The translation of ambiguous text presents a challenge for translation systems, as it requires using the surrounding context to disambiguate the intended meaning as much as possible. While prior work has studied ambiguities that result from different grammatical features of the source and target lan…

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