Video generation models (VGMs) offer strong spatiotemporal priors for embodied observation--action modeling. However, joint-space action vectors lack explicit image-space structure and vary in dimensionality and semantics across embodiments, making it challenging to directly leverage the rich spatiotemporal priors of V...
Xiang-Yu Zhu, Jin Xu, Yue (Sophie) Guo et al.· 0 citations
Evaluation of Computer-Use Agents (CUAs) is often limited to the final deliverables they create (at the end of hundreds of steps) and assessed with functional verifiers, as seen in OSWorld. However, such evaluation of end-state performance lacks transparency into how and why agents fail in various tasks, obfuscating cr...
Zhi-Lin Wang, Shao-Kun Zhang, Yi-Fan Zhang et al.· 0 citations
Omni Demand Understanding is established as a distinct multimodal contextual inference problem: given an interaction stream, a model must detect whether a user demand is present and infer intent from multimodal and conversational context, and ODU is evaluated along five dimensions, covering both single-turn and multi-t...
Qi Chen, Yun-Fei Chu, Haolin He et al.· 1 citation· ⚡1
Trie-GRPO, a novel reinforcement learning algorithm based on action prefix trees, which enables step-level advantage estimation, is introduced, which resolves the credit assignment problem by isolating intermediate correct decisions from downstream errors, while effectively balancing exploration efficiency and depth co...
Fei-Fan Wang, Zong-Bing Zhang, Yu Zhang et al.· 0 citations
NebulaVLA is presented, an asynchronous dual-frequency architecture that decouples high-level semantic reasoning from low-level action control, optimizing computational resources and modularity and introduces GESTURE-7, a unified language-grounded action representation.
Congyu Zhao, Shuai Tian, Xu Zhang et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
