{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/2"}],"enrichment":{"capability":"Evaluates mathematical expressions from LLM outputs by parsing LaTeX and plain expressions, converting them to a common symbolic form, and comparing them against gold-standard answers for equivalence.","skillfed_tags":["llm-evaluation","symbolic-math","batch-grading"],"use_cases":["Evaluate LLM outputs on standardized math benchmarks (MATH, GSM8K, AMC, AIME) to measure model reasoning accuracy.","Grade student or model answers in educational platforms where answers may be written in multiple equivalent forms.","Batch-process CSV files of model predictions and gold answers to identify systematic evaluation errors in existing pipelines.","Extract and normalize mathematical answers from unstructured LLM outputs before feeding them to downstream grading systems.","Compare symbolic expressions for equivalence in automated homework or quiz systems that accept multiple valid forms."],"what_it_does":"Math-Verify is a mathematical expression evaluator built to assess LLM outputs on math tasks. It solves the problem that existing evaluators often fail due to strict format requirements, limited parsing, or inflexible comparison logic\u2014sometimes underestimating model performance significantly. The package works in three stages: extracting answers from model output using regex patterns with configurable priority, parsing extracted text (including LaTeX and plain expressions) into a common SymPy representation while normalizing malformations and handling special cases like percentages and complex numbers, and finally comparing the parsed answer to a gold standard using both symbolic and numerical methods.\n\nThe parser supports three extraction targets (LaTeX, plain expressions, and literal strings) and handles a wide range of mathematical constructs: set theory, intervals, equations, inequalities, matrices, complex numbers, and relations. Comparison is intelligent\u2014it recognizes equivalent forms (e.g., a + b equals b + a), handles precision-based numeric equality, and includes special logic for sets, intervals, and flipped inequalities. The package is designed for researchers and developers evaluating LLM math reasoning, with optional command-line tools for batch evaluation on datasets like MATH-Hard, MATH-500, GSM8K, AMC23, and AIME24.","worth_installing":"Yes, with conditions. Install if you need to evaluate LLM math outputs and can work with Python >= 3.10; the package has low install friction, no known vulnerabilities, and outperforms existing evaluators on MATH dataset. Do not install if you require ongoing active development\u2014the package is aging (last commit 2026-01-10) and may not receive rapid updates for new edge cases or datasets."},"id":"math-verify","links":{"html":"https://skillfed.io/packages/math-verify","md":"https://skillfed.io/packages/math-verify.md","pypi":"https://pypi.org/project/math-verify/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2026-01-10","license_spdx":null,"license_treatment":"permissive","name":"math-verify","python_support":"supports_current","summary":"HuggingFace library for verifying mathematical answers"},"popularity":{"monthly_downloads":3283852,"position":2675,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.9.0"}