4 citations · 4 across the 7 of their papers we have counts for
7 papers
Building Comparative Motivation Profiles with Instrumental Interventions
David Vella Zarb, Rustem Turtayev, Taywon Min +2
Safety evaluations often infer latent motivations from behavioral patterns, but the construct validity of these inferences is unclear. We study this problem in alignment faking, wh…
Capability Provenance in Language Models: A Case Study in Social Reasoning
Glenn Matlin, Chandreyi Chakraborty, Saehee Eom +8
We use training-data attribution as an interpretable tool for capability discovery, mapping which regions of the pretraining corpus support social reasoning versus STEM reasoning i…
Quality over Quantity: Demonstration Curation via Influence Functions for Data-Centric Robot Learning
Haeone Lee, Taywon Min, Junsu Kim +4
Learning from demonstrations has emerged as a promising paradigm for end-to-end robot control, particularly when scaled to diverse and large datasets. However, the quality of demon…
Entropy-Aware On-Policy Distillation of Language Models
Woogyeol Jin, Taywon Min, Yongjin Yang +5
On-policy distillation is a promising approach for transferring knowledge between language models, where a student learns from dense token-level signals along its own trajectories.…
Unintended Misalignment from Agentic Fine-Tuning: Risks and Mitigation
Dongyoon Hahm, Taywon Min, Woogyeol Jin +1
Beyond simple text generation, Large Language Models (LLMs) have evolved into agentic systems capable of planning and interacting with external tools to solve complex tasks. This e…
Understanding Impact of Human Feedback via Influence Functions
Taywon Min, Haeone Lee, Yongchan Kwon +1
In Reinforcement Learning from Human Feedback (RLHF), it is crucial to learn suitable reward models from human feedback to align large language models (LLMs) with human intentions.…
Benchmarking Mobile Device Control Agents across Diverse Configurations
Juyong Lee, Taywon Min, Minyong An +4
Mobile device control agents can largely enhance user interactions and productivity by automating daily tasks. However, despite growing interest in developing practical agents, the…