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Sixu Yan

4 accepted papers

2026

M3Bench: Benchmarking Whole-Body Motion Generation for Mobile Manipulation in 3D Scenes

ICRA 2026poster

We propose M3Bench, a new benchmark for whole-body motion generation in mobile manipulation tasks. Given a 3D scene context, M3Bench requires an embodied agent to reason about its configuration, environmental constraints, and task objectives to generate coordinated whole-body motion trajectories for…

2026

ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving

ICLR 2026poster

Recent studies have explored leveraging the world knowledge and cognitive capabilities of Vision-Language Models (VLMs) to address the long-tail problem in end-to-end autonomous driving. However, existing methods typically formulate trajectory planning as a language modeling task, where physical act…

Cited by 0SourcecodeScholar
2025

DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving

CVPR 2025highlight

Recently, the diffusion model has emerged as a powerful generative technique for robotic policy learning, capable of modeling multi-mode action distributions. Leveraging its capability for end-to-end autonomous driving is a promising direction. However, the numerous denoising steps in the robotic di…

2025

M${}{3}$Bench: Benchmarking Whole-Body Motion Generation for Mobile Manipulation in 3D Scenes

RA-L 2025

We propose M <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${}^{3}$</tex-math></inline-formula> Bench, a new benchmark for whole-body motion generation in mobile manipulation tasks. Given a 3D scene context, M <in

Cited by 4SourceScholar