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20242026
most citedGrounded Answers for Multi-agent Decision-making Problem through Generative World Model

1 citations · 1 across the 14 of their papers we have counts for

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cs.RO2026

Phase-Conditioned Affordance Fields for SE(3)-Equivariant Visuomotor Policies

Xinzhe Chen, Liqi Huang, Sihua Ren +5

SE(3)-equivariance provides a useful geometric inductive bias for visuomotor policies, encoding that actions covary with rigid transformations of the observation. However, existing…

cs.RO2026

OASIS: Observation-Action Space Alignment via SE(3) Trajectory Prediction for Robotic Manipulation

Xinzhe Chen, Sihua Ren, Liqi Huang +5

Recent vision-language-action (VLA) models and world action models (WAMs) advance robotic manipulation by enriching intermediate representations with auxiliary spatial features or…

cs.RO2026

AffordSim: A Scalable Data Generator and Benchmark for Affordance-Aware Robotic Manipulation

Mingyang Li, Haofan Xu, Haowen Sun +10

Many everyday robot manipulation skills are affordance-dependent, with success determined by whether the robot contacts the functional object region required by the subsequent acti…

cs.RO2026

ECHO: Continuous Hierarchical Memory for Vision-Language-Action Models

Yanbin Hu, Jin Cui, Jiayi Lu +6

Memory capacity is a critical factor determining the performance of Vision-Language-Action (VLA) models in long-horizon manipulation tasks. Existing memory-augmented architectures…

cs.RO2026

Toward Reliable Sim-to-Real Predictability for MoE-based Robust Quadrupedal Locomotion

Tianyang Wu, Hanwei Guo, Yuhang Wang +6

Reinforcement learning has shown strong promise for quadrupedal agile locomotion, even with proprioception-only sensing. In practice, however, sim-to-real gap and reward overfittin…

cs.RO2025

Bridging Simulation and Reality: Cross-Domain Transfer with Semantic 2D Gaussian Splatting

Jian Tang, Pu Pang, Haowen Sun +4

Cross-domain transfer in robotic manipulation remains a longstanding challenge due to the significant domain gap between simulated and real-world environments. Existing methods suc…

cs.RO2025

PRISM: Projection-based Reward Integration for Scene-Aware Real-to-Sim-to-Real Transfer with Few Demonstrations

Haowen Sun, Han Wang, Chengzhong Ma +4

Learning from few demonstrations to develop policies robust to variations in robot initial positions and object poses is a problem of significant practical interest in robotics. Co…