activity
20232026
most citedPlayFusion: Skill Acquisition via Diffusion from Language-Annotated Play

3 citations · 5 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2026

Expanding the Capabilities of Reinforcement Learning via Text Feedback

Yuda Song, Lili Chen, Fahim Tajwar +5

The success of RL for LLM post-training stems from an unreasonably uninformative source: a single bit of information per rollout as binary reward or preference label. At the other…

cs.LG2025

Generative Classifiers Avoid Shortcut Solutions

Alexander C. Li, Ananya Kumar, Deepak Pathak

Discriminative approaches to classification often learn shortcuts that hold in-distribution but fail even under minor distribution shift. This failure mode stems from an overrelian…

cs.RO2025

ViPRA: Video Prediction for Robot Actions

Sandeep Routray, Hengkai Pan, Unnat Jain +2

Can we turn a video prediction model into a robot policy? Videos, including those of humans or teleoperated robots, capture rich physical interactions. However, most of them lack l…

cs.RO2025

LocoFormer: Generalist Locomotion via Long-context Adaptation

Min Liu, Deepak Pathak, Ananye Agarwal

Modern locomotion controllers are manually tuned for specific embodiments. We present LocoFormer, a generalist omni-bodied locomotion model that can control previously unseen legge…

cs.RO2025

Towards Embodiment Scaling Laws in Robot Locomotion

Bo Ai, Liu Dai, Nico Bohlinger +7

Cross-embodiment generalization underpins the vision of building generalist embodied agents for any robot, yet its enabling factors remain poorly understood. We investigate embodim…

cs.RO2024

Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer

Xingyu Liu, Deepak Pathak, Ding Zhao

We investigate the problem of transferring an expert policy from a source robot to multiple different robots. To solve this problem, we propose a method named - that…

cs.RO2023★ 3 cited

PlayFusion: Skill Acquisition via Diffusion from Language-Annotated Play

Lili Chen, Shikhar Bahl, Deepak Pathak

Learning from unstructured and uncurated data has become the dominant paradigm for generative approaches in language and vision. Such unstructured and unguided behavior data, commo…

cs.RO2023★ 2 cited

DEFT: Dexterous Fine-Tuning for Real-World Hand Policies

Aditya Kannan, Kenneth Shaw, Shikhar Bahl +2

Dexterity is often seen as a cornerstone of complex manipulation. Humans are able to perform a host of skills with their hands, from making food to operating tools. In this paper,…