a benchmark designed to evaluate large language models (LLMs) specifically in their ability to answer real-world coding-related questions.

benchmark designed to evaluate large language models (LLMs) on solving complex, college-level scientific problems from domains like chemistry, physics, and mathematics.

a meta-benchmark that evaluates how well factuality evaluators assess the outputs of large language models (LLMs).

focuses on understanding how these models perform in various scenarios and analyzing results from an interpretability perspective.

a benchmark for evaluating the performance of large language models (LLMs) in various tasks related to both textual and visual imagination.

a multimodal question-answering benchmark designed to evaluate AI models' cognitive ability to understand human beliefs and goals.