24 citations · 29 across the 22 of their papers we have counts for
7 papers · 1 filter
Self-Supervised Keyframe Discovery for Horizon-Invariant Behavior Cloning
Prabin Kumar Rath, Omkar Patil, Nakul Gopalan
Behavior cloning (BC) in non-Markovian environments is a challenging problem because policies have to reason over contextual information over long horizons. Existing policy archite…
Monkey See, Can Monkey Do? A Benchmark for Evaluating Robot Skill Learning by Observation
Weiwei Gu, Anmol Gupta, Anant Sah +5
Learning from Observation (LfO) is a fundamental robotic capability that replicates how humans and animals socially learn from each other. Beyond its biological parallels, this mod…
Spec2Cov: An Agentic Framework for Code Coverage Closure of Digital Hardware Designs
Sean Lowe, Elias Hilaneh, Alma Babbit +3
Hardware verification is one of the most challenging stages of the hardware design process, requiring significant time and resources to ensure a design is fully validated and produ…
Meanings and Measurements: Multi-Agent Probabilistic Grounding for Vision-Language Navigation
Swagat Padhan, Lakshya Jain, Bhavya Minesh Shah +3
Robots collaborating with humans must convert natural language goals into actionable, physically grounded decisions. For example, executing a command such as "go two meters to the…
StageCraft: Execution Aware Mitigation of Distractor and Obstruction Failures in VLA Models
Kartikay Milind Pangaonkar, Prabin Rath, Omkar Patil +1
Large scale pre-training on text and image data along with diverse robot demonstrations has helped Vision Language Action models (VLAs) to generalize to novel tasks, objects and sc…
You've Got a Golden Ticket: Improving Generative Robot Policies With A Single Noise Vector
Omkar Patil, Ondrej Biza, Thomas Weng +9
Generative robot policies trained on demonstrations using behavior cloning often learn actions that are sub-optimal or misaligned with respect to the downstream task. Policy improv…
PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations
Anmol Gupta, Weiwei Gu, Omkar Patil +2
Articulation modeling enables robots to learn joint parameters of articulated objects for effective manipulation which can then be used downstream for skill learning or planning. E…