Pai 的 AI 雷达

机器人具身

今天:Matrix-Game 3.5(Agent 原型),Lies We Can See(Agent 原型)。并行还有 LightNav-0、Lucida、Not All Agreement。

日期
2026/09/01
今日条目
78
当前类目
12
#01

Matrix-Game 3.5: Enhancing Real-Time Streaming Interactive World Models with Patch Memory

Interactive world models extend video generation from offline clip synthesis toward persistent simulation of interactive virtual worlds, enabling applications in games, robotics, embodied agents, and XR. Achieving stable

推荐理由Matrix-Game 3.5: Enhancing Real-Time:Interactive world models extend video generation from offline clip synthesis toward。
模型与评测机器人具身HF daily papers
#02

Lies We Can See: Joint Verbal and Non-Verbal Deception by VLM Agents in Embodied Social Interactions

Strategic deception by LLM and VLM agents has emerged as a central AI alignment and safety concern. Social-deduction games (where each player holds a hidden role and communicates with others to deduce identities) serve a

推荐理由Lies We Can See: Joint Verbal:Strategic deception by LLM and VLM agents has emerged as a central AI alignment。
模型与评测机器人具身HF daily papers
#03

LightNav-0: Eliciting VLM Spatial Intelligence for Generalist Embodied Navigation

Embodied navigation requires agents to translate heterogeneous goals and visual observations into actions across tasks, environments, and robot embodiments. Modern vision-language models (VLMs) already encode spatial pri

推荐理由LightNav-0: Eliciting VLM Spatial:Embodied navigation requires agents to translate heterogeneous goals and visual。
模型与评测机器人具身HF daily papers
#04

Lucida: Parse, Generate, and Place for Composable Real-to-Sim Scene Modeling

Composable scene modeling aims to recover a real indoor scene as complete, editable object assets arranged as observed, giving robot simulation and embodied AI a simulation-ready replica of the real environment whose obj

推荐理由Lucida: Parse, Generate, and Place:Composable scene modeling aims to recover a real indoor scene as complete, editable。
模型与评测机器人具身HF daily papers