DocVQA

A multimodal benchmark for evaluating models on complex tasks spanning diverse academic disciplines and requiring both visual and textual reasoning.

A benchmark for evaluating multimodal large language models across a broad range of vision-language tasks and capabilities.

An evaluation method in which human reviewers assess the quality of AI system outputs against defined criteria such as correctness, relevance, helpfulness, safety, or fluency, providing judgments that complement or validate automated evaluation metrics.

An evaluation method that measures model output quality by comparing generated responses against ground-truth reference data or golden datasets.