Danny Driess
21 papers · 2020–2025 · 6 venues · across top CS/AI venues
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Achievements
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Research topics
Artificial Intelligence
(14)
Core AI
(14)
Deep Learning
(8)
Machine Learning
(7)
Reinforcement Learning
(5)
Core Methods
(5)
Applications Β· Reinforcement Learning
(4)
Learning Types
(4)
Models
(3)
Computer Vision
(2)
Natural Language Processing
(2)
Robotics
(2)
Application Areas
(2)
Applications Β· Robotics
(2)
Capabilities
(2)
Keywords
robot manipulation
(2)
representation learning
(2)
large language model
(2)
neural radiance field
(2)
in-context learning
(2)
zero-shot learning
(2)
vision-language model
(2)
vision-language-action model
(2)
robotic manipulation
(2)
robotic control
(2)
reinforcement learning
(2)
visual question answering
(1)
scene understanding
(1)
interpretability
(1)
reasoning
(1)
path planning
(1)
embodied ai
(1)
contrastive learning
(1)
multimodal learning
(1)
text generation
(1)
Papers
Ο_0.5: a Vision-Language-Action Model with Open-World Generalization
CoRL 2025
Direct Motion Models for Assessing Generated Videos
ICML 2025
FAST: Efficient Action Tokenization for Vision-Language-Action Models
RSS 2025
Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models
ICML 2025
Training Strategies for Efficient Embodied Reasoning
CoRL 2025
Vision Language Models are In-Context Value Learners
ICLR 2025
Οβ: A Vision-Language-Action Flow Model for General Robot Control
RSS 2025
ALOHA Unleashed: A Simple Recipe for Robot Dexterity
CoRL 2024
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
ICML 2024
Vid2Robot: End-to-end Video-conditioned Policy Learning with Cross-Attention Transformers
RSS 2024
Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents
NeurIPS 2023
Large Language Models as General Pattern Machines
CoRL 2023
PaLM-E: An Embodied Multimodal Language Model
ICML 2023
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
CoRL 2023
Learning Multi-Object Dynamics with Compositional Neural Radiance Fields
CoRL 2022
Reinforcement Learning with Neural Radiance Fields
NeurIPS 2022
Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning
CoRL 2021
Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics
NeurIPS 2021
Structured deep generative models for sampling on constraint manifolds in sequential manipulation
CoRL 2021
Adaptive Discretization for Evaluation of Probabilistic Cost Functions
AISTATS 2020
Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image
RSS 2020