RoboSpatialチャレンジ技術報告：選択的推論活性化と参照フレーム曖昧性解消による身体化空間推論
Technical Report of RoboSpatial Challenge at CVPR 2026: Selective Reasoning Activation and Reference-Frame Disambiguation for Embodied Spatial Reasoning
CVPR 2026のRoboSpatialチャレンジで1位を獲得した、ロボットの空間推論を強化する推論時プロンプト手法を提案した論文。
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著者: Yuxiang Xie, Qi Lv, Jianming Xing, Zijian Hong, Xiang Deng, Weili Guan, Liqiang Nie
分類: cs.CV
原文アブストラクト
Vision-language models achieve strong general perception but often struggle with the spatial reasoning required for embodied tasks. We present RoboSpatialBrain, our submission to the RoboSpatial Challenge at the Embodied Reasoning in Action Workshop, CVPR 2026, built on RoboBrain2.5-8B-NV. RoboSpatialBrain combines two training-free, inference-time mechanisms: a forced <think> prefix activation strategy paired with a task-specific post-prompt that elicits deliberate reasoning on context and compatibility tasks, and an explicit reference-frame redirection pipeline that resolves camera-centric and object-centric ambiguity for context tasks. We additionally explore fine-tuning RoboBrain2.5 on compatibility data and present a detailed analysis of its interaction with prompting. RoboSpatialBrain achieved first place in the RoboSpatial Challenge, with an overall success rate of 80.9\% on RoboSpatial-Home. Code is available at https://github.com/YuxiangXie2003/RoboSpatialBrain.
