4 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.RO2026
Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons
Anthony Liang, Yigit Korkmaz, Jiahui Zhang +14
General-purpose robot reward models are typically trained to predict absolute task progress from expert demonstrations, providing only local, frame-level supervision. While effecti…
cs.RO2024★ 4 cited
MotIF: Motion Instruction Fine-tuning
Minyoung Hwang, Joey Hejna, Dorsa Sadigh +1
While success in many robotics tasks can be determined by only observing the final state and how it differs from the initial state - e.g., if an apple is picked up - many tasks req…
cs.CV2023
Promptable Behaviors: Personalizing Multi-Objective Rewards from Human Preferences
Minyoung Hwang, Luca Weihs, Chanwoo Park +3
Customizing robotic behaviors to be aligned with diverse human preferences is an underexplored challenge in the field of embodied AI. In this paper, we present Promptable Behaviors…