arXiv:2607. 02466v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are fundamentally bottlenecked by the scarcity of expert demonstrations -- triplets of observations, instructions, and actions that are costly to collect at scale.
By Junhao Shi, Siyin Wang, Xiaopeng Yu, Li Ji, Jingjing Gong, Xipeng Qiu
The paper proposes a method to train efficient multi‑task manipulation policies by distilling knowledge from single‑task Conditional Flow Matching (CFM) experts. Instead of training separate models for each task, the authors transfer the experts’ learned velocity fields into a shared policy, combining this distillation signal with the original CFM objective. Experiments on RLBench demonstrate that this approach improves multi‑task performance while keeping the model size fixed, avoiding the need for larger capacity or performance drops seen with naive concatenated training.
By Shreya Deshmukh, Imen Mahdi, Nick Heppert, Abhinav Valada
arXiv:2608.30760v1 Announce Type: new
Abstract: Recent studies have shown that multimodal large language models (MLLMs) can serve as embodied agents, translating language instructions and visual obse...
By Ziyi Bai, Siqi Li, Tinglei Huang, B\"orje F. Karlsson
arXiv:2606. 30266v1 Announce Type: cross Abstract: Motion-language agents must possess the bidirectional capability to both understand human movement (motion-to-text, M2T) and generate it from natural language (text-to-motion, T2M).
By Bertram Taetz, Hugo Albuquerque Cosme da Silva, Gabriele Bleser-Taetz
arXiv:2606. 31980v1 Announce Type: cross Abstract: Agents are increasingly capable of automating software tasks, but can they teach humans how to use software themselves?
By Meng Chen, Anya Ji, Tsung-Han Wu, Tobias Maringgele, David M. Chan, Alane Suhr, Amy Pavel
arXiv:2610.01652v1 Announce Type: cross
Abstract: Structured policies improve efficiency, robustness, and interpretability in imitation learning by introducing task-specific inductive bias, but exist...
By Feiyu Gavin Zhu, Qi Xu, Zhifei Deng, Zhigang Hua, Luke Simon, Jean Oh, Reid Simmons