7 papers
Latent Memory Palace: Reasoning for Control as Autoregressive Variational Inference
Chuning Zhu, Eva Xu, Jose Barreiros +3
Human decision-making is highly flexible -- some actions are taken immediately; others require longer deliberation. Language models have exhibited a similar capacity for adaptive "…
Difference-Aware Retrieval Policies for Imitation Learning
Quinn Pfeifer, Ethan Pronovost, Paarth Shah +3
Parametric imitation learning via behavior cloning can suffer from poor generalization to out-of-distribution states due to compounding errors during deployment. We show that reusi…
Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons
Anthony Liang, Yigit Korkmaz, Jiahui Zhang +14
General-purpose robot reward models are typically trained to predict absolute task progress from expert demonstrations, providing only local, frame-level supervision. While effecti…
Operator-Theoretic Foundations and Policy Gradient Methods for General MDPs with Unbounded Costs
Abhishek Gupta, Aditya Mahajan
Markov decision processes (MDPs) is viewed as an optimization of an objective function over certain linear operators over general function spaces. A new existence result is establi…
Semantic World Models
Jacob Berg, Chuning Zhu, Yanda Bao +2
Planning with world models offers a powerful paradigm for robotic control. Conventional approaches train a model to predict future frames conditioned on current frames and actions,…
Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets
Chuning Zhu, Raymond Yu, Siyuan Feng +3
Imitation learning has emerged as a promising approach towards building generalist robots. However, scaling imitation learning for large robot foundation models remains challenging…