4 citations · 6 across the 5 of their papers we have counts for
5 papers
Potential-Guided Particle Steering for Negation-Constrained Dexterous Grasping
Geonho Kim, SooGon Kim, Jongmin Lee
Language-driven dexterous grasp models, such as DextER, perform well when instructions specify where to grasp, but we find they fail systematically when an instruction also specifi…
A Regret Minimization Framework on Preference Learning in Large Language Models
Suhwan Kim, Taehyun Cho, Geon-Hyeong Kim +4
Reinforcement learning with verifiable rewards (RLVR) has enabled progress on reasoning-intensive tasks by relying on task-specific verifiers that provide automated correctness sig…
SafeDPO: A Simple Approach to Direct Preference Optimization with Enhanced Safety
Geon-Hyeong Kim, Yu Jin Kim, Byoungjip Kim +4
As Large Language Models (LLMs) are increasingly deployed in real-world applications, balancing helpfulness and safety has become a central challenge. A natural approach is to inco…
LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation
Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang +2
We consider the problem of learning from observation (LfO), in which the agent aims to mimic the expert's behavior from the state-only demonstrations by experts. We additionally as…
Variational Interaction Information Maximization for Cross-domain Disentanglement
HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong +1
Cross-domain disentanglement is the problem of learning representations partitioned into domain-invariant and domain-specific representations, which is a key to successful domain t…