2 papers
cs.CL2026
CPR for LLMs: Critical-Point Routing against Catastrophic Forgetting in Domain Adaptation
Kwangmin Ki, Yunhun Nam, Jongheon Jeong +1
Supervised fine-tuning (SFT) is the de facto standard for adapting large language models (LLMs) to target domains, but it often degrades the model's general capabilities, a phenome…
cs.CL2025
When to Ensemble: Identifying Token-Level Points for Stable and Fast LLM Ensembling
Heecheol Yun, Kwangmin Ki, Junghyun Lee +1
Ensembling Large Language Models (LLMs) has gained attention as a promising approach to surpass the performance of individual models by leveraging their complementary strengths. In…