Cover Image

GEMINUS: Dual-aware Global and Scene-Adaptive Mixture-of-Experts for End-to-End Autonomous Driving

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wan, Chi, Cui, Yixin, Du, Jiatong, Yang, Shuo, Bai, Yulong, Yi, Peng, Li, Nan, Huang, Yanjun
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Robotics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Continual Adaptation for Autonomous Driving with the Mixture of Progressive Experts Network
by: Cui, Yixin, et al.
Published: (2025)

A Unified Candidate Set with Scene-Adaptive Refinement via Diffusion for End-to-End Autonomous Driving
by: Wu, Zhengfei, et al.
Published: (2026)

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving
by: Feng, Renju, et al.
Published: (2025)

Driving in Corner Case: A Real-World Adversarial Closed-Loop Evaluation Platform for End-to-End Autonomous Driving
by: Geng, Jiaheng, et al.
Published: (2025)

DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving
by: Yang, Zhenjie, et al.
Published: (2025)

A Knowledge-Driven Diffusion Policy for End-to-End Autonomous Driving Based on Expert Routing
by: Xu, Chengkai, et al.
Published: (2025)

FlowDrive: Energy Flow Field for End-to-End Autonomous Driving
by: Jiang, Hao, et al.
Published: (2025)

PIE: Perception and Interaction Enhanced End-to-End Motion Planning for Autonomous Driving
by: Yuan, Chengran, et al.
Published: (2025)

FeaXDrive: Feasibility-aware Trajectory-Centric Diffusion Planning for End-to-End Autonomous Driving
by: Wang, Baoyun, et al.
Published: (2026)

Causality-Aware End-to-End Autonomous Driving via Ego-Centric Joint Scene Modeling
by: Moon, Seokha, et al.
Published: (2026)

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects
by: Cui, Yixin, et al.
Published: (2025)

SUPER-AD: Semantic Uncertainty-aware Planning for End-to-End Robust Autonomous Driving
by: Ryu, Wonjeong, et al.
Published: (2025)

Bridging Past and Future: End-to-End Autonomous Driving with Historical Prediction and Planning
by: Zhang, Bozhou, et al.
Published: (2025)

CoReVLA: A Dual-Stage End-to-End Autonomous Driving Framework for Long-Tail Scenarios via Collect-and-Refine
by: Fang, Shiyu, et al.
Published: (2025)

VECTOR-Drive: Tightly Coupled Vision-Language and Trajectory Expert Routing for End-to-End Autonomous Driving
by: Zhao, Rui, et al.
Published: (2026)

TeraSim-World: Worldwide Safety-Critical Data Synthesis for End-to-End Autonomous Driving
by: Wang, Jiawei, et al.
Published: (2025)

Exploring the Causality of End-to-End Autonomous Driving
by: Li, Jiankun, et al.
Published: (2024)

DriveSafer: End-to-End Autonomous Driving with Safety Guidance
by: Sural, Shounak, et al.
Published: (2026)

ComDrive: Comfort-Oriented End-to-End Autonomous Driving
by: Wang, Junming, et al.
Published: (2024)

Unleashing the Potential of Diffusion Models for End-to-End Autonomous Driving
by: Zheng, Yinan, et al.
Published: (2026)

Reinforced Refinement with Self-Aware Expansion for End-to-End Autonomous Driving
by: Liu, Haochen, et al.
Published: (2025)

DRAMA: An Efficient End-to-end Motion Planner for Autonomous Driving with Mamba
by: Yuan, Chengran, et al.
Published: (2024)

Pseudo-Expert Regularized Offline RL for End-to-End Autonomous Driving in Photorealistic Closed-Loop Environments
by: Noguchi, Chihiro, et al.
Published: (2025)

OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Driving
by: Xing, Shuo, et al.
Published: (2024)

ExpertAD: Enhancing Autonomous Driving Systems with Mixture of Experts
by: Jiang, Haowen, et al.
Published: (2025)

Enhanced Safety in Autonomous Driving: Integrating Latent State Diffusion Model for End-to-End Navigation
by: Chu, Detian, et al.
Published: (2024)

DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving
by: Liao, Bencheng, et al.
Published: (2024)

NetRoller: Interfacing General and Specialized Models for End-to-End Autonomous Driving
by: Xin, Ren, et al.
Published: (2025)

Don't Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Driving
by: Song, Ziying, et al.
Published: (2025)

IDOL: Inverse-Dynamics-Guided Future Prediction for End-to-End Autonomous Driving
by: Zhang, Chenghao, et al.
Published: (2026)

Data Scaling Laws for Imitation Learning-Based End-to-End Autonomous Driving
by: Zheng, Yupeng, et al.
Published: (2024)

LeGo-Drive: Language-enhanced Goal-oriented Closed-Loop End-to-End Autonomous Driving
by: Paul, Pranjal, et al.
Published: (2024)

Prioritizing Perception-Guided Self-Supervision: A New Paradigm for Causal Modeling in End-to-End Autonomous Driving
by: Huang, Yi, et al.
Published: (2025)

Exploring Contextual Representation and Multi-Modality for End-to-End Autonomous Driving
by: Azam, Shoaib, et al.
Published: (2022)

Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Driving
by: Atakishiyev, Shahin, et al.
Published: (2024)

LightEMMA: Lightweight End-to-End Multimodal Model for Autonomous Driving
by: Qiao, Zhijie, et al.
Published: (2025)

End-To-End Planning of Autonomous Driving in Industry and Academia: 2022-2023
by: Lan, Gongjin, et al.
Published: (2023)

FocalAD: Local Motion Planning for End-to-End Autonomous Driving
by: Sun, Bin, et al.
Published: (2025)

Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving
by: Hua, Zhihua, et al.
Published: (2026)

AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving
by: Wu, Yanhao, et al.
Published: (2026)