Papers by Jinho Choo

2 papers
SCALE: Upscaled Continual Learning of Large Language Models (2026.findings-acl)

Copied to clipboard

Challenge: Recent discussions suggest that further progress will come from scaling the right structure, not merely parameters or data, while preserving acquired knowledge.
Approach: They propose a width upscaling architecture that inserts lightweight expansions into linear modules while freezing all pre-trained parameters.
Outcome: The proposed architecture reduces severe forgetting while learning new knowledge on a controlled synthetic biography benchmark.
TLPO: Token-Level Policy Optimization for Mitigating Language Confusion in Large Language Models (2026.acl-long)

Copied to clipboard

Challenge: Prior mitigation approaches that optimize entire responses operate at the level of entire responses and can lead to unintended degradation of general model capabilities.
Approach: They propose a fine-tuning framework to mitigate erroneous outputs by localizing and updating the policy at a granular level.
Outcome: The proposed framework outperforms baselines on multiple multilingual LLMs across diverse languages while preserving task accuracy.

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