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Data · dataset · 2026

DogNeverSleep/Artifact-Bench

Listed in Hugging Face Datasets

Description

Artifact-Bench Paper | Github Artifact-Bench is a comprehensive benchmark for evaluating whether Multimodal Large Language Models (MLLMs) can truly detect and reason about the artifacts of AI-generated videos. Instead of focusing only on semantic understanding, Artifact-Bench emphasizes artifact-aware realism perception and fine-grained video analysis across photorealistic, animated, and CG-style domains. Tasks Artifact-Bench defines three complementary tasks: Task… See the full description on the dataset page: huggingface.co/datasets/DogNeverSleep/Artifact-Bench.

Links

Documentation and papers

Catalogue records · 1

Topics

Stated by source
video · video text to text
Inferred from text
Video 75%
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
Hugging Face DatasetsDogNeverSleep/Artifact-Bench11 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].hf_modality:videosource · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].local:modality:videoenrichment · Hugging Facekeyword-concept-rules@1.0.0title+description (75%)
concepts[task].hf_task:video-text-to-textsource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
license_textsource · Hugging Faceconnector:huggingface@1.0.0
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0