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20242026
most citedGenAD: Generative End-to-End Autonomous Driving

3 citations · 9 across the 23 of their papers we have counts for

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13 papers · 1 filter

cs.CL2026

On-Policy Distillation for Vision-Language Model Adaptation, an Effective Paradigm on Low-Quality Multimodal Data

Hongyuan Zhang, Xianda Guo, Yanlun Peng +6

Knowledge distillation offers an efficient route to transfer a task-adapted vision-language teacher to a compact student. The training target in current vision-language distillatio…

cs.AI2026

DriveCache: Action-Aware Caching for Driving World Model Inference

Jianchun Yang, Jian Liang, Xianda Guo +5

Driving video generation models support autonomous-driving development by predicting controllable future scenes for simulation, planning evaluation, and offline data generation. Di…

cs.RO2026

DreamWAM: Beyond RGB Future Prediction for World Action Models

Shanglin Yuan, Weiheng Zhao, Xin Shi +6

World Action Models (WAMs) learn action-relevant representations by predicting how the observed world will evolve. Most existing WAMs define this future in RGB space, where task-re…

cs.RO2026

EA-Nav: Learning Safe Visual Navigation Policies with Embodiment Awareness

Jialu Zhang, Yong Du, Xianda Guo +6

Cross-embodiment navigation is a key challenge in embodied intelligence. Due to differences in embodiment, the same visual observation may imply different actions for different age…

cs.RO2026

SkillNav: Score-Level Skill Intervention for Zero-Shot Object Goal Navigation

Ruijie Sang, Yiqun Duan, Pinhan Fu +3

Vision-Language Model (VLM) agents have advanced zero-shot object-goal navigation, yet single-frame reasoning leaves them without the cross-step behavioral awareness an embodied na…

cs.RO2026

TrustVLA: Mechanism-Guided Inference-Time Defense Against Vision-Language-Action Backdoors

Pinhan Fu, Xianda Guo, Xuetao Li +5

Vision-Language-Action (VLA) models are deployed through pipelines that end users cannot audit, and a poisoned VLA can behave normally on clean observations while a small visual tr…

cs.RO2026

Humanoid-OmniOcc: Stereo-Based Full-View Occupancy Dataset for Embodied AI

Xianda Guo, Bohao Zhang, Chenwei Huang +6

Occupancy prediction at voxel-level granularity is essential for safe robotic navigation and interaction in complex environments. Existing occupancy datasets, however, are predomin…

cs.CV2026

StereoFactory: A Unified Merging Framework for Robust Stereo Matching

Xianda Guo, Pinhan Fu, Ruilin Wang +3

Stereo matching has advanced through foundation models trained on large-scale datasets, yet this paradigm suffers from a scalability bottleneck: incorporating new data requires cos…

cs.RO2026

ReactSim-Bench: Benchmarking Reactive Behavior World Model Simulation in Autonomous Driving

Zhiyuan Zhang, Yanlun Peng, Jianing Zhang +7

Reactive capability is a key property of data-driven behavior world model simulators for autonomous driving simulation systems. With this capability, simulated world agents can res…

cs.RO2026

MotionVLA: Injecting Geometric Motion into Vision-Language-Action Model

Shanglin Yuan, Weiheng Zhao, Xianda Guo +4

Vision-language-action (VLA) models increasingly condition robot policies on history, depth, or 4D features to resolve ambiguity in long-horizon manipulation. However, more spatiot…

cs.RO2026

Bench2Drive-Robust: Benchmarking Closed-Loop Autonomous Driving under Deployment Perturbations

Zhiyuan Zhang, Zhenghao Jin, Yanlun Peng +8

Robustness is a critical requirement for deploying autonomous driving systems in the real world. Existing robustness benchmarks for autonomous driving have made important progress…

cs.RO2026

R3DP: Real-Time 3D-Aware Policy for Embodied Manipulation

Yuhao Zhang, Wanxi Dong, Yue Shi +13

Embodied manipulation requires accurate 3D understanding of objects and their spatial relations to plan and execute contact-rich actions. While large-scale 3D vision models provide…

cs.RO2026

UniVTAC: A Unified Simulation Platform for Visuo-Tactile Manipulation Data Generation, Learning, and Benchmarking

Baijun Chen, Weijie Wan, Tianxing Chen +13

Robotic manipulation has seen rapid progress with vision-language-action (VLA) policies. However, visuo-tactile perception is critical for contact-rich manipulation, as tasks such…