Sign inGet started
Dataset · Hugging Face

COREVQA2025/COREVQA

COREVQA: A Crowd Observation and Reasoning Entailment Visual Question Answering Benchmark Paper: https://www.arxiv.org/abs/2507.13405 Repository: https://github.com/corevqa/COREVQA Demo: https://colab.research.google.com/drive/1SpuTta5tSzktiCo9xN4CtE9P1pmYV0ax CrowdHuman Dataset Homepage: https://www.crowdhuman.org/ Abstract Recently, many benchmarks and datasets have been developed to evaluate Vision-Language Models (VLMs) using visual question answering (VQA)… See the full description on the dataset page: https://huggingface.co/datasets/COREVQA2025/COREVQA.

Author / organizationCOREVQA2025
Downloads250 (as reported by Hugging Face)
Likes4
Created30 June 2025
Last updated at source11 August 2025
visual-question-answeringvisual-entailmentbinary-classificationreasoningmultimodalfine-grained-analysistext-comprehensioncrowdscrowd-humanhuman-centricdense-scenesocclusionreal-worldsynthetic-dataadversarialchallengingtrue-falsecomplex-statementsvlm-evaluationbenchmarkrobustnessmodel-failure-analysisspatial-reasoningnegation-handling
Embed this entry
<iframe src="https://silytics.si/embed/item/cf4769ad-26bc-4262-9c9c-9191aaad0910" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Popularity, last 3 days

250 now (-3 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 Information may be incomplete or out of date.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 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.