VoxAfford fuses multi-scale voxel features into MLLM output tokens using cross-attention with a learned compatibility gate to achieve SOTA open-vocabulary 3D affordance detection with ~8% mIoU gain and zero-shot robot transfer.
Afford-x: Generalizable and slim affordance reasoning for task-oriented manipulation
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UNVERDICTED 3representative citing papers
SeqWM introduces sequential autoregressive agent-wise world models for multi-robot MBRL, outperforming baselines in performance and sample efficiency on Bi-DexHands and Multi-Quadruped tasks with physical robot deployment.
Proposes Modality-Aware Credit Assignment (MoCA) with blindfolded-reasoning proxy to reward perception fidelity separately from reasoning in VLMs.
citing papers explorer
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VoxAfford: Multi-Scale Voxel-Token Fusion for Open-Vocabulary 3D Affordance Detection
VoxAfford fuses multi-scale voxel features into MLLM output tokens using cross-attention with a learned compatibility gate to achieve SOTA open-vocabulary 3D affordance detection with ~8% mIoU gain and zero-shot robot transfer.
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Empowering Multi-Robot Cooperation via Sequential World Models
SeqWM introduces sequential autoregressive agent-wise world models for multi-robot MBRL, outperforming baselines in performance and sample efficiency on Bi-DexHands and Multi-Quadruped tasks with physical robot deployment.
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Bad Seeing or Bad Thinking? Rewarding Perception for Multimodal Reasoning
Proposes Modality-Aware Credit Assignment (MoCA) with blindfolded-reasoning proxy to reward perception fidelity separately from reasoning in VLMs.