Homer Walke

Orcid: 0000-0002-8148-1437

Affiliations:
  • UC Berkeley, CA, USA


According to our database1, Homer Walke authored at least 23 papers between 2020 and 2025.

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Bibliography

2025
Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better.
CoRR, May, 2025

π<sub>0.5</sub>: a Vision-Language-Action Model with Open-World Generalization.
CoRR, April, 2025

2024
KALIE: Fine-Tuning Vision-Language Models for Open-World Manipulation without Robot Data.
CoRR, 2024

Octo: An Open-Source Generalist Robot Policy.
CoRR, 2024

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.
CoRR, 2024

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.
Proceedings of the Robotics: Science and Systems XX, 2024


Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration.
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Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Autonomous Improvement of Instruction Following Skills via Foundation Models.
Proceedings of the Conference on Robot Learning, 6-9 November 2024, Munich, Germany., 2024

Evaluating Real-World Robot Manipulation Policies in Simulation.
Proceedings of the Conference on Robot Learning, 6-9 November 2024, Munich, Germany., 2024

Scaling Cross-Embodied Learning: One Policy for Manipulation, Navigation, Locomotion and Aviation.
Proceedings of the Conference on Robot Learning, 6-9 November 2024, Munich, Germany., 2024

2023
Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models.
CoRR, 2023

Open X-Embodiment: Robotic Learning Datasets and RT-X Models.
CoRR, 2023

Stabilizing Contrastive RL: Techniques for Offline Goal Reaching.
CoRR, 2023

BridgeData V2: A Dataset for Robot Learning at Scale.
Proceedings of the Conference on Robot Learning, 2023

Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control.
Proceedings of the Conference on Robot Learning, 2023

2022
PLAD: Learning to Infer Shape Programs with Pseudo-Labels and Approximate Distributions.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Don't Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning.
Proceedings of the Conference on Robot Learning, 2022

Generalization with Lossy Affordances: Leveraging Broad Offline Data for Learning Visuomotor Tasks.
Proceedings of the Conference on Robot Learning, 2022

2021
Learning Finite Linear Temporal Logic Specifications with a Specialized Neural Operator.
CoRR, 2021

2020
Learning to Infer Shape Programs Using Latent Execution Self Training.
CoRR, 2020


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