TIGER-Lab/general-verifier

The TIGER-Lab/general-verifier is a 1.5 billion parameter causal language model developed by TIGER-Lab, specifically designed for verifying the equivalence of mathematical expressions. With a context length of 131072 tokens, this model excels at determining if a student's answer matches a ground truth answer without solving the problem itself. It is primarily optimized for robust verification tasks in mathematical reasoning, making it distinct from general-purpose LLMs.