Yecheng Jason Ma

According to our database1, Yecheng Jason Ma authored at least 28 papers between 2020 and 2024.

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Bibliography

2024
Eurekaverse: Environment Curriculum Generation via Large Language Models.
CoRR, 2024

On-Robot Reinforcement Learning with Goal-Contrastive Rewards.
CoRR, 2024

Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model.
CoRR, 2024

DrEureka: Language Model Guided Sim-To-Real Transfer.
CoRR, 2024

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

Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models.
Proceedings of the IEEE International Conference on Robotics and Automation, 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

Universal Visual Decomposer: Long-Horizon Manipulation Made Easy.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Eureka: Human-Level Reward Design via Coding Large Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
LIV: Language-Image Representations and Rewards for Robotic Control.
CoRR, 2023

TOM: Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching.
CoRR, 2023

Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
CoRR, 2023

Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching.
Proceedings of the Learning for Dynamics and Control Conference, 2023

LIV: Language-Image Representations and Rewards for Robotic Control.
Proceedings of the International Conference on Machine Learning, 2023

VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Uniformly Conservative Exploration in Reinforcement Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
How Far I'll Go: Offline Goal-Conditioned Reinforcement Learning via f-Advantage Regression.
CoRR, 2022

SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching.
CoRR, 2022

Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Regret Bounds for Risk-Sensitive Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching.
Proceedings of the International Conference on Machine Learning, 2022

Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Safe Human-Interactive Control via Shielding.
CoRR, 2021

Conservative Offline Distributional Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

State Relevance for Off-Policy Evaluation.
Proceedings of the 38th International Conference on Machine Learning, 2021

Likelihood-Based Diverse Sampling for Trajectory Forecasting.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Diverse Sampling for Normalizing Flow Based Trajectory Forecasting.
CoRR, 2020


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