Generalist robot policies offer strong behavioral priors, but achieving deployment-level reliability and throughput remains difficult. Reinforcement learning (RL) can improve these policies, yet its effectiveness is constrained by the cost of online interaction. Existing methods adapt frozen flow-matching policies by t...
Carl Qi, Wei-Jun Dong, Xiao-Jie Wang et al.· 0 citations
Motivated by the human ability to integrate experience across language, perception, and action, we introduce UniWALM, a unified world-action-language model that learns video, action, and language in a single shared representation, where each modality is both a conditioning signal and a supervision target. We ask: can j...
Rahul Sajnani, D. Romeres, Ming-Yuan Zhang et al.· 0 citations
This approach introduces the first modality-agnostic interface for localized multimodal control in a DiT without retraining the base model from scratch, offering a simple and extensible path toward precise, region-aware, multimodal guidance in generative image synthesis.
Rahul Sajnani, Yulia Gryaditskaya, R. Měch et al.· arXiv.org· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.