Evaluate reward models for math reasoning
Retrain models for new data at edge devices
Open Persian LLM Leaderboard
Evaluate code generation with diverse feedback types
Compare code model performance on benchmarks
Optimize and train foundation models using IBM's FMS
Launch web-based model application
Display benchmark results
Measure execution times of BERT models using WebGPU and WASM
Convert a Stable Diffusion XL checkpoint to Diffusers and open a PR
Display genomic embedding leaderboard
Analyze model errors with interactive pages
Evaluate LLM over-refusal rates with OR-Bench
Project RewardMATH is a platform designed to evaluate and benchmark reward models used for math reasoning. It focuses on assessing AI models' ability to solve mathematical problems while emphasizing correctness, logical reasoning, and efficiency. The tool is invaluable for researchers and developers aiming to refine their models' performance in mathematical problem-solving.
What makes Project RewardMATH unique?
Project RewardMATH is specifically designed for math reasoning, offering tailored benchmarks and insights that general-purpose evaluation tools cannot match.
What formats does Project RewardMATH support for input?
It supports LaTeX for math problem inputs, ensuring compatibility with standard mathematical notation.
Is Project RewardMATH available for public use?
Yes, Project RewardMATH is available for researchers and developers. Access details can be found on the official project website.