World Action Modeling with Progressive Visual Planning
World action models (WAMs) have emerged as a promising paradigm for robotic control by jointly predicting future visu...
每天自动聚合 AI 领域最新动态
World action models (WAMs) have emerged as a promising paradigm for robotic control by jointly predicting future visu...
Natural-language service requests can require a language-model decision before execution starts, consuming part of th...
When a camera revisits a previously observed region, a video world model should reproduce what was there before. This...
Before invoking external tools, an agentic LLM must select among a K-way action space: executing a call, seeking clar...
Furnished floor plans support real-estate visualization, interior design, and architectural workflows, yet automatic ...
LLM agents generate intermediate reasoning and actions token by token, making extended interactions slow and computat...
Transferring human motion to humanoid robots requires adapting the demonstrated motion to the robot morphology while ...
Looped Transformers achieve parameter efficiency by repeatedly executing a shared block across recurrent loops. Each ...
On-policy self-distillation has recently emerged as an effective approach for improving language-model reasoning by s...
Recent video-based world models pair the scalability of autoregressive (AR) prediction with the visual quality of dif...
Coding agents are beginning to move beyond purely digital tasks to tackle physical-world challenges, particularly in ...
On-policy learning has been argued to reduce catastrophic forgetting, produce sparser parameter updates, and improve ...