3 papers
cs.AI2026
Lifted State Hypothesis in Large Language Models
Bumjin Park, Jaesik Choi
Large language models (LLMs) adapt rapidly through fine-tuning and in-context learning, yet it remains unclear which inputs they treat as the same case and why their predictions ch…
cs.AI2026
Incomplete Prompt Jailbreaks in Large Language Models
Yeonjea Kim, Bumjin Park, Jaesik Choi
Large language models (LLMs) are increasingly released as open-weight models with safeguards against harmful requests. Nevertheless, sentence completion remains vulnerable to incom…
cs.CL2025
Deontological Keyword Bias: The Impact of Modal Expressions on Normative Judgments of Language Models
Bumjin Park, Jinsil Lee, Jaesik Choi
Large language models (LLMs) are increasingly engaging in moral and ethical reasoning, where criteria for judgment are often unclear, even for humans. While LLM alignment studies c…