7 citations · 7 across the 10 of their papers we have counts for
5 papers · 1 filter
Assessing LLM Reasoning Steps via Principal Knowledge Grounding
Hyeon Hwang, Yewon Cho, Chanwoong Yoon +5
Step-by-step reasoning has become a standard approach for large language models (LLMs) to tackle complex tasks. While this paradigm has proven effective, it raises a fundamental qu…
ASGuard: Activation-Scaling Guard to Mitigate Targeted Jailbreaking Attack
Yein Park, Jungwoo Park, Jaewoo Kang
Large language models (LLMs), despite being safety-aligned, exhibit brittle refusal behaviors that can be circumvented by simple linguistic changes. As tense jailbreaking demonstra…
Thinking Sparks!: Emergent Attention Heads in Reasoning Models During Post Training
Yein Park, Minbyul Jeong, Jaewoo Kang
The remarkable capabilities of modern large reasoning models are largely unlocked through post-training techniques such as supervised fine-tuning (SFT) and reinforcement learning (…
CoTox: Chain-of-Thought-Based Molecular Toxicity Reasoning and Prediction
Jueon Park, Yein Park, Minju Song +4
Drug toxicity remains a major challenge in pharmaceutical development. Recent machine learning models have improved in silico toxicity prediction, but their reliance on annotated d…
Does Time Have Its Place? Temporal Heads: Where Language Models Recall Time-specific Information
Yein Park, Chanwoong Yoon, Jungwoo Park +2
While the ability of language models to elicit facts has been widely investigated, how they handle temporally changing facts remains underexplored. We discover Temporal Heads, spec…