Cover Image

ETA: Efficiency through Thinking Ahead, A Dual Approach to Self-Driving with Large Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hamdan, Shadi, Sima, Chonghao, Yang, Zetong, Li, Hongyang, Güney, Fatma
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

CarFormer: Self-Driving with Learned Object-Centric Representations
by: Hamdan, Shadi, et al.
Published: (2024)

Hint-AD: Holistically Aligned Interpretability in End-to-End Autonomous Driving
by: Ding, Kairui, et al.
Published: (2024)

Centaur: Robust End-to-End Autonomous Driving with Test-Time Training
by: Sima, Chonghao, et al.
Published: (2025)

Thinking Ahead: Foresight Intelligence in MLLMs and World Models
by: Gong, Zhantao, et al.
Published: (2025)

Test-time Correction: An Online 3D Detection System via Visual Prompting
by: Zhang, Hanxue, et al.
Published: (2024)

FLARE: Learning Future-Aware Latent Representations from Vision-Language Models for Autonomous Driving
by: Xie, Chengen, et al.
Published: (2026)

Improving VQA Reliability: A Dual-Assessment Approach with Self-Reflection and Cross-Model Verification
by: Wu, Xixian, et al.
Published: (2025)

Enhancing Self-Driving Segmentation in Adverse Weather Conditions: A Dual Uncertainty-Aware Training Approach to SAM Optimization
by: Ravindran, Dharsan, et al.
Published: (2025)

CoWorld-VLA: Thinking in a Multi-Expert World Model for Autonomous Driving
by: Huang, Minqing, et al.
Published: (2026)

Think Before You Drive: World Model-Inspired Multimodal Grounding for Autonomous Vehicles
by: Liao, Haicheng, et al.
Published: (2025)

Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability
by: Gao, Shenyuan, et al.
Published: (2024)

Visual Point Cloud Forecasting enables Scalable Autonomous Driving
by: Yang, Zetong, et al.
Published: (2023)

Understand, Think, and Answer: Advancing Visual Reasoning with Large Multimodal Models
by: Zhan, Yufei, et al.
Published: (2025)

Think as Needed: Geometry-Driven Adaptive Perception for Autonomous Driving
by: Kim, Donghyun, et al.
Published: (2026)

Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving
by: Mei, Jianbiao, et al.
Published: (2024)

K-MaT: Knowledge-Anchored Manifold Transport for Cross-Modal Prompt Learning in Medical Imaging
by: Zeng, Jiajun, et al.
Published: (2026)

DriveLM: Driving with Graph Visual Question Answering
by: Sima, Chonghao, et al.
Published: (2023)

HTMA-Net: Towards Multiplication-Avoiding Neural Networks via Hadamard Transform and In-Memory Computing
by: Hamdan, Emadeldeen, et al.
Published: (2025)

Leveraging Chat-Based Large Vision Language Models for Multimodal Out-Of-Context Detection
by: Shalabi, Fatma, et al.
Published: (2024)

ETA: Energy-based Test-time Adaptation for Depth Completion
by: Chung, Younjoon, et al.
Published: (2025)

Assessing Color Vision Test in Large Vision-language Models
by: Ye, Hongfei, et al.
Published: (2025)

Enhancing Spatial Reasoning through Visual and Textual Thinking
by: Liang, Xun, et al.
Published: (2025)

Navigation with VLM framework: Towards Going to Any Language
by: Yin, Zecheng, et al.
Published: (2024)

Poster: Camera Tampering Detection for Outdoor IoT Systems
by: Attarha, Shadi, et al.
Published: (2026)

Unified Attention Modeling for Efficient Free-Viewing and Visual Search via Shared Representations
by: Mohammed, Fatma Youssef, et al.
Published: (2025)

A Likelihood Ratio-Based Approach to Segmenting Unknown Objects
by: Nayal, Nazir, et al.
Published: (2024)

Addressing Corner Cases in Autonomous Driving: A World Model-based Approach with Mixture of Experts and LLMs
by: Liao, Haicheng, et al.
Published: (2025)

Hybrid Reasoning Based on Large Language Models for Autonomous Car Driving
by: Azarafza, Mehdi, et al.
Published: (2024)

SUDER: Self-Improving Unified Large Multimodal Models for Understanding and Generation with Dual Self-Rewards
by: Hong, Jixiang, et al.
Published: (2025)

S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Modelwith Spatio-Temporal Visual Representation
by: Xie, Yichen, et al.
Published: (2025)

Research on Driving Scenario Technology Based on Multimodal Large Lauguage Model Optimization
by: Mengjie, Wang, et al.
Published: (2025)

INSIGHT: Enhancing Autonomous Driving Safety through Vision-Language Models on Context-Aware Hazard Detection and Edge Case Evaluation
by: Chen, Dianwei, et al.
Published: (2025)

O1O: Grouping of Known Classes to Identify Unknown Objects as Odd-One-Out
by: Yavuz, Mısra, et al.
Published: (2024)

AHA -- Predicting What Matters Next: Online Highlight Detection Without Looking Ahead
by: Chang, Aiden, et al.
Published: (2025)

Dual Thinking and Logical Processing -- Are Multi-modal Large Language Models Closing the Gap with Human Vision ?
by: Dayanandan, Kailas, et al.
Published: (2024)

CLASP: Class-Adaptive Layer Fusion and Dual-Stage Pruning for Multimodal Large Language Models
by: Dang, Yunkai, et al.
Published: (2026)

AEMIM: Adversarial Examples Meet Masked Image Modeling
by: Xiang, Wenzhao, et al.
Published: (2024)

DriveGazen: Event-Based Driving Status Recognition using Conventional Camera
by: Yang, Xiaoyin
Published: (2024)

Enhancing Vision-Language Models for Autonomous Driving through Task-Specific Prompting and Spatial Reasoning
by: Wu, Aodi, et al.
Published: (2025)

Toward Automatic Safe Driving Instruction: A Large-Scale Vision Language Model Approach
by: Sakajo, Haruki, et al.
Published: (2025)