Jesse Zhang PRO

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authored 2 papers 3 months ago

HAMSTER: Hierarchical Action Models For Open-World Robot Manipulation

Paper • 2502.05485 • Published Feb 8

PEEK: Guiding and Minimal Image Representations for Zero-Shot Generalization of Robot Manipulation Policies

Paper • 2509.18282 • Published Sep 22 • 1

authored 2 papers 7 months ago

ReWiND: Language-Guided Rewards Teach Robot Policies without New Demonstrations

Paper • 2505.10911 • Published May 16 • 1

HAND Me the Data: Fast Robot Adaptation via Hand Path Retrieval

Paper • 2505.20455 • Published May 26

authored 4 papers almost 2 years ago

TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models

Paper • 2310.05905 • Published Oct 9, 2023 • 2

RoboCLIP: One Demonstration is Enough to Learn Robot Policies

Paper • 2310.07899 • Published Oct 11, 2023

RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback

Paper • 2402.03681 • Published Feb 6, 2024

Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance

Paper • 2310.10021 • Published Oct 16, 2023 • 2

authored a paper over 2 years ago

SPRINT: Scalable Policy Pre-Training via Language Instruction Relabeling

Paper • 2306.11886 • Published Jun 20, 2023