arXiv 2610.27040 · cs.RO · 2026-10-19
ACE-Brain-0.6: Scaling Spatial Grounding for Physical Foundation Models
Yinhe Wang, Tao Tao, Zexin He, Shuang Luo, Wei Mao, Yao Mu, Feng Pan, Hanming Deng 等 14 人
ACE Robotics
在最新榜 #361 本站收录于 2026-10-26
一句话要点
ACE-Brain-0.6 通过扩大视觉定位数据来增强具身模型的空间感知：把机器人操作录像与其他视觉数据自动标注成可验证的定位监督，用约 150 万样本微调 Qwen3.5-9B 得到。
ACE-Brain-0.6 scales visual grounding for embodied models, converting robot manipulation recordings and other visual data into verifiable grounding supervision and fine-tuning Qwen3.5-9B on about 1.5 million samples.
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主题与学科
同主题：机器人与具身
- Has GPT-6-Astra Achieved Embodied Intelligence? ▲421
- In-Context Learning for Robots: Methods and Applications ▲388
- GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives ▲310
- HexaShell: A Thin Harness for Exploring the Limits of VLM Agents as Robot Coding Agents ▲294
- Reflex: Visually Grounded Reactive Humanoid Control ▲154
同主题：多模态
- StreamEval: Evaluating Interactive Streaming Video Generation Models 2026-10-20 · ▲649
- MJev-Spatial: System One Spatial Intelligence via Native Attention Matching 2026-10-15 · ▲556
- Omni-IO Skills: Harnessing Your Agent Omni-Native 2026-09-25 · ▲485
- LoopVL: Recurrent Visual Intelligence 2026-09-29 · ▲417
- VideoJev: System One Model for Video Understanding and Interaction 2026-10-13 · ▲375
数据说明
元数据来自 arXiv API（已核实）；点赞来自 Hugging Face 每日论文；引用来自 Semantic Scholar。最近刷新 2026-10-26。
要点由本站根据摘要自写，不转载摘要原文，请阅读原文。