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20232025
most citedEvaluation of Large Language Models for Decision Making in Autonomous Driving

6 citations · 8 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos

Fanheng Kong, Jingyuan Zhang, Hongzhi Zhang +7

Videos are unique in their integration of temporal elements, including camera, scene, action, and attribute, along with their dynamic relationships over time. However, existing ben…

cs.CV2024★ 1 cited

CoVLA: Comprehensive Vision-Language-Action Dataset for Autonomous Driving

Hidehisa Arai, Keita Miwa, Kento Sasaki +4

Autonomous driving, particularly navigating complex and unanticipated scenarios, demands sophisticated reasoning and planning capabilities. While Multi-modal Large Language Models…

cs.CV2024★ 1 cited

Heron-Bench: A Benchmark for Evaluating Vision Language Models in Japanese

Yuichi Inoue, Kento Sasaki, Yuma Ochi +3

Vision Language Models (VLMs) have undergone a rapid evolution, giving rise to significant advancements in the realm of multimodal understanding tasks. However, the majority of the…

cs.CV2023

NuScenes-MQA: Integrated Evaluation of Captions and QA for Autonomous Driving Datasets using Markup Annotations

Yuichi Inoue, Yuki Yada, Kotaro Tanahashi +1

Visual Question Answering (VQA) is one of the most important tasks in autonomous driving, which requires accurate recognition and complex situation evaluations. However, datasets a…

cs.CV2023★ 6 cited

Evaluation of Large Language Models for Decision Making in Autonomous Driving

Kotaro Tanahashi, Yuichi Inoue, Yu Yamaguchi +11

Various methods have been proposed for utilizing Large Language Models (LLMs) in autonomous driving. One strategy of using LLMs for autonomous driving involves inputting surroundin…