15 citations · 21 across the 14 of their papers we have counts for
5 papers · 1 filter
CoHuB: A Simulation Benchmark for Multi-Humanoid Collaboration
Hyunjin Park, Jebeom Chae, Minwoo Park +11
Many physical tasks in human environments require collaboration, from assisting a partner to jointly manipulating an object. Yet, existing humanoid benchmarks largely focus on sing…
Collision Snapshot Guided Time-Reversed Safety-Critical Scenario Generation
Taehyung Kim, Jongeun Choi
The generation of safety-critical traffic scenarios is essential for training and evaluating autonomous vehicles. Prior approaches typically perturb the trajectories of existing ag…
To Go Far, Go Together: Diverse Preferences Induce a Curriculum for Reward Optimization
Taehyung Kim, Jongeun Choi
Learning a reward model from human feedback and optimizing a policy against it is one approach to aligning AI systems with individual users. From a fairness perspective, existing w…
Deployable Human Preference Alignment in Robotics: Learning Representative Rewards from Diverse Human Preferences
Taehyung Kim, Gwangmo Lee, Minjun Chang +2
Aligning robot policies with human preferences is essential for deployment to diverse end users. In per-user alignment approach, preference feedback is often sparse, so learning be…
Group-Invariant Unsupervised Skill Discovery: Symmetry-aware Skill Representations for Generalizable Behavior
Junwoo Chang, Joseph Park, Roberto Horowitz +2
Unsupervised skill discovery aims to acquire behavior primitives that improve exploration and accelerate downstream task learning. However, existing approaches often ignore the geo…