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ReMoMask-2, a structure-aware RAG framework coupling Hierarchical Bidirectional Momentum contrastive learning to align global and part-level features with text; Semantic Spatial-Temporal Attention (SSTA) for topology-aware fusion; and Topology Structured Masking (TSM) to force robust part-level grounding via adaptive masking are introduced.
This work proposes MobileVLA-R1 2.0, an RL-enhanced VLA framework that explicitly couples structured embodied reasoning with executable mobile robot control, and introduces a reasoning-conditioned action decoder that maps multimodal reasoning representations to task-level action targets, which are subsequently translated into embodiment-specific commands by robot controllers.
VaseMuseum not only enhances the reliability of digital museum interactions but also reduces hallucinations and improves citation validity in knowledge-intensive contexts.
Geometry-aware reconstruction reduces hallucinations in object poses, leading to more reliable robot planning.
Surpassing existing benchmarks, SpatialAvatar-0 achieves superior 4D head avatar quality with up to 60x fewer training iterations than traditional methods.
Forget fragmented architectures: UniMesh lets you edit 3D meshes iteratively with semantic prompts, bridging the gap between generation and understanding.
