BABA(US:BABA) 机器之心·2025-07-03 08:01Core Viewpoint - Alibaba's Damo Academy has introduced WorldVLA, a model that integrates World Model and Action Model into a unified autoregressive framework, enhancing understanding and generation across text, images, and actions [1][4]. Summary by Sections Research Overview - The development of Vision-Language-Action (VLA) models has become a significant focus in robotic action modeling, typically built on large-scale pretrained multimodal language models (MLLMs) with added action output capabilities [4]. - Existing VLA models often lack a deep understanding of actions, treating them merely as output rather than analyzing them as input [5]. Model Description - WorldVLA addresses the limitations of both VLA and World Models by using a unified autoregressive mechanism for action and image understanding and generation [5][10]. - It employs three independent encoders for processing images, text, and action data, sharing the same vocabulary to facilitate cross-modal tasks [12]. Mechanism and Strategy - The World Model component generates visual representations based on input actions, learning the physical dynamics of the environment, while the Action Model enhances visual understanding [7]. - An action attention masking strategy is introduced to mitigate error accumulation during the generation of multiple actions, significantly improving performance in action chunking tasks [8][14]. Experimental Results - In the LIBERO benchmark, WorldVLA achieved a 4% improvement in grasp success rate compared to traditional action models and a 10% reduction in Fréchet Video Distance (FVD) compared to traditional world models [8]. - The introduction of the attention mask strategy led to a performance improvement in grasp success rates ranging from 4% to 23% in action chunking tasks [8]. Comparative Analysis - WorldVLA outperformed other models in various metrics, demonstrating its effectiveness in integrating action and world modeling [18]. - The model's ability to generate the next frame based on actions and images showcases its advanced capabilities in visual prediction [24].