Dataset · Hugging Face

eddyhkchiu/V2V-GoT-QA

Name: V2V-GoT-QA
Creator: eddyhkchiu
License: apache-2.0
Keywords: task_categories:image-text-to-text, license:apache-2.0, arxiv:2509.18053, region:us, robotics, autonomous-driving, cooperative-autonomous-driving, physical-ai, reasoning-ai, graph-of-thoughts, chain-of-thoughts, computer-vision, multimodal-llm, mllm

V2V-GoT-QA Paper | Code Our V2V-GoT-QA is a dataset for Multimodal LLM-based cooperative autonomous driving with graph-of-thoughts reasoning. V2V-GoT-QA includes 9 different types of perception, prediction, and planning QA tasks, with 110K training and 31K testing QA pairs. Dataset Details Our V2V-GoT-QA includes three stages: Occlusion-aware Perception (Q1 - Q4): consider visible, occluding, and invisible objects. Planning-aware Prediction (Q5 - Q7): include… See the full description on the dataset page: https://huggingface.co/datasets/eddyhkchiu/V2V-GoT-QA.

View on Hugging FaceReport an issue

Author / organization	eddyhkchiu
License (as declared)	apache-2.0
Downloads	143 (as reported by Hugging Face)
Likes	5
Created	17 October 2025
Last updated at source	17 February 2026

roboticsautonomous-drivingcooperative-autonomous-drivingphysical-aireasoning-aigraph-of-thoughtschain-of-thoughtscomputer-visionmultimodal-llmmllm

Embed this entry

<iframe src="https://silytics.si/embed/item/b9b35610-54ab-432f-a336-9062fb4c39ae" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Popularity, last 2 days

143 now (+1 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.