Yevgen Chebotar
収録論文 31本 ・ フィジカルAI/ロボット学習
※arXiv著者名で収集。同姓同名の別人の論文が含まれる場合があります。
論文
- RoboTTT: Context Scaling for Robot Policies2026/7/16
- RoboTTT: Context Scaling for Robot Policies2026/7/1
- Vesta: A Generalist Embodied Reasoning Model2026/6/1
- World Action Models are Zero-shot Policies2026/2/17
- World Action Models are Zero-shot Policies2026/2/1
- RT-H: Action Hierarchies Using Language2024/3/1
- Open X-Embodiment: Robotic Learning Datasets and RT-X Models2023/10/1
- Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions2023/9/1
- Robotic Offline RL from Internet Videos via Value-Function Pre-Training2023/9/1
- RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control2023/7/28
- RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control2023/7/1
- Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators2023/5/1
- PaLM-E: An Embodied Multimodal Language Model2023/3/1
- RT-1: Robotics Transformer for Real-World Control at Scale2022/12/1
- Inner Monologue: Embodied Reasoning through Planning with Language Models2022/7/1
- Do As I Can, Not As I Say: Grounding Language in Robotic Affordances2022/4/1
- How to Leverage Unlabeled Data in Offline Reinforcement Learning2022/2/1
- AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale2021/11/1
- Conservative Data Sharing for Multi-Task Offline Reinforcement Learning2021/9/1
- Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills2021/4/1
- MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale2021/4/1
- Visionary: Vision architecture discovery for robot learning2021/3/1
- Supervised Learning and Reinforcement Learning of Feedback Models for Reactive Behaviors: Tactile Feedback Testbed2020/7/1
- Meta-Learning via Learned Loss2019/6/1
- Learning Latent Space Dynamics for Tactile Servoing2018/11/1
- Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience2018/10/1
- Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets2017/5/1
- Time-Contrastive Networks: Self-Supervised Learning from Video2017/4/1
- Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning2017/3/1
- Path Integral Guided Policy Search2016/10/1
- Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search2016/10/1