Best AI tools for< Math Reasoning Evaluation >

AI Math is an online math solver that uses artificial intelligence to help users solve math problems. It can solve a wide range of math problems, including arithmetic, algebra, geometry, trigonometry, calculus, combinations, word problems, statistics, and probability. AI Math is available in over 30 languages and is free to use. It is a valuable tool for students, educators, and anyone who needs help with math.

AI MathGPT is an AI-powered math tutoring tool designed to assist students and parents with math homework. It offers advanced reasoning, step-by-step solutions, and clear explanations for challenging math problems. The tool aims to boost math performance, provide 24/7 support, and enhance math learning experiences for users of all levels.

OpenAI01.net is an AI tool that offers free usage with some limitations. It provides a new series of AI models designed to spend more time thinking before responding, capable of reasoning through complex tasks and solving harder problems in science, coding, and math. Users can ask questions and get answers for free, with the option to select different models based on credits. The tool excels in complex reasoning tasks and has shown impressive performance in various benchmarks.

Kie.ai is an AI platform that offers access to DeepSeek R1 & V3 APIs for secure and scalable AI solutions. It provides advanced reasoning models for tasks in math, coding, and language, along with versatile natural language processing capabilities. With no local deployment required, developers can easily integrate the APIs into their projects for fast and efficient AI solutions. Kie.ai ensures data security by hosting the APIs on U.S.-based servers, offering affordable pricing plans and comprehensive documentation for seamless integration.

AI Math Coach is an AI-powered platform designed to revolutionize math learning by providing personalized and engaging math practice for students. The tool creates custom math worksheets aligned with classroom learning, offers a free trial for users to experience its features, and empowers parents to enhance their child's math skills through AI-driven practices. With features like personalized challenges, progress tracking, and seamless transition from classroom to home, AI Math Coach simplifies math practice and makes it enjoyable for both parents and students.

MATH (ML & AI Technology Hub) is a premier innovation hub and ecosystem enabler based in T-Hub, Hyderabad. It serves as a Centre of Excellence for Machine Learning and Artificial Intelligence, connecting startups, academia, government, and industry giants. MATH offers a dynamic space, physical resources, and a thriving ecosystem to incubate startups in various sectors. The hub aims to foster AI innovation, empower startups, and create job opportunities in the AI field by 2025.

Math Sniper is an AI-powered application designed to provide precise math solutions, exam preparation assistance, and exploration of mathematical concepts. The app offers step-by-step solutions to math challenges at all levels, connects users with math tutors for personalized help, and covers a wide range of subjects beyond mathematics, such as biology, chemistry, physics, history, economics, and language tasks. With features like Snap & Ask for instant answers, step-by-step explanations, and a user-friendly interface, Math Sniper aims to enhance users' understanding of complex concepts and facilitate learning in various disciplines.

Math.bot is an advanced AI math solver powered by GPT-4o, offering fast and accurate solutions to a wide range of math problems. The platform integrates leading technologies like Microsoft Math Solver, providing free and user-friendly services accessible via web and mobile apps. Users can solve math equations and word problems with detailed step-by-step guidance, upload math problems for instant AI-assisted solutions, and engage with an interactive ChatGPT math solver for dynamic learning experiences.

Math.now is a free online math AI solver powered by Math GPT, offering instant, step-by-step solutions for a wide range of mathematical problems. Users can input math problems or upload photos for analysis, interact with the math AI bot for explanations, and receive real-time assistance. The application supports algebra, geometry, calculus, and word problems, providing detailed guidance and personalized learning experiences. Math.now's AI solver ensures accuracy, efficiency, and accessibility for students, educators, and self-learners.

Rank Math is an AI-powered SEO tool that helps you optimize your website for search engines. It offers a variety of features to help you improve your website's ranking, including keyword research, on-page optimization, and link building. Rank Math also provides detailed analytics to help you track your progress and identify areas for improvement.

AI Math Solver is an advanced AI application that leverages multi-modal AI technology to assist users in solving math problems step by step. Users can upload photos or describe math problems to receive accurate solutions efficiently. The application also supports Latex for displaying math formulas, allows users to save and share solved math problems, and offers solutions for set operations, equations, and geometry problems. AI Math Solver is designed to outperform human performance in math challenges, making it a powerful tool for students and professionals alike.

MathGPT is an AI math solver and calculator that provides users with the ability to solve various mathematical problems, including calculations, derivatives, and integrations. It also offers a question notebook feature and AI tutoring capabilities. Users can input mathematical expressions and equations, and MathGPT will provide step-by-step solutions and answers. The tool supports a wide range of mathematical functions and constants, making it a versatile and efficient tool for students, educators, and anyone needing assistance with math problems.

SnapXam is an AI-powered math tutor that helps students learn math and physics step-by-step. It offers a variety of features, including a math solver, step-by-step solutions, and video explanations. SnapXam is available on iOS and Android devices.

Synthesis Tutor is an AI-powered math tutoring application designed for children aged 5-11. It offers personalized math learning experiences, immediate evaluation and adaptation, unlimited practice, and active engagement. The application aims to build deep understanding and confidence in math through a multisensory experience. Synthesis Tutor goes beyond rote memorization, empowering children to explore, understand, and excel in math. It provides 1-on-1 attention, fills gaps in knowledge, and offers immersive, engaging, and fun learning experiences.

Interactive Mathematics is an online platform that provides math problem-solving help, tutoring, and lessons. It offers an AI-powered math problem solver that provides step-by-step answers to math homework problems. The platform also offers on-demand math tutoring, where students can send their math problems to tutors and receive immediate help. Interactive Mathematics also provides a variety of math lessons, covering topics from basic algebra to calculus. The platform is designed to help students improve their math grades and understanding.

Photomath is the ultimate math help app designed to assist learners of all levels, from elementary through college, in understanding and solving math problems. The app provides step-by-step explanations, allows users to scan problems, offers multiple solution methods, and encourages learning through detailed explanations. Photomath aims to help users build their math skills and confidence by providing personalized math assistance anytime, anywhere. With millions of learners benefiting from its features monthly, Photomath is a valuable tool for anyone seeking math support.

Mathful is a free online AI math solver that provides step-by-step solutions to math problems of various types and difficulty levels. It covers a wide range of math topics, from elementary math to calculus, and is designed to help students better understand math concepts, improve their math skills, and prepare for math tests. Mathful's AI-powered math solver is highly accurate and efficient, providing detailed explanations and calculations to help users master math problems effectively.

MathSolver.top is an AI math solver and personalized math tutor application that offers a free platform for solving math problems with high accuracy. Users can upload math questions and receive step-by-step answers instantly. The application includes features like Homework Helper Mode, Tutor/Learner Mode, and the ability to scan/upload/copy math problems for quick solutions. It provides personalized progressive learning through AI-generated study sets and smart recommendations for daily tasks. MathSolver aims to enhance math learning by offering a user-friendly interface and efficient problem-solving capabilities.

Worksheep is an AI-powered tool that allows users to create math worksheets instantly. By leveraging artificial intelligence technology, users can generate customized math exercises efficiently. The platform streamlines the process of worksheet creation, saving time for educators and parents. With a user-friendly interface, Worksheep simplifies the task of producing math problems for various educational purposes.

MyMathSolver.ai is an AI math solver powered by Math GPT models like GPT-4o, providing comprehensive assistance across various math topics. Users can easily access detailed, step-by-step solutions to complex math problems using versatile input methods such as text, images, PDFs, or CSV files. The platform offers interactive problem-solving through a math AI bot and ensures accessibility on various devices and operating systems. With features like math AI bot, math solver online free access, and math GPT for advanced solutions, MyMathSolver.ai transforms the learning journey for students and math enthusiasts.

Evalchemy is a unified and easy-to-use toolkit for evaluating language models, focusing on post-trained models. It integrates multiple existing benchmarks such as RepoBench, AlpacaEval, and ZeroEval. Key features include unified installation, parallel evaluation, simplified usage, and results management. Users can run various benchmarks with a consistent command-line interface and track results locally or integrate with a database for systematic tracking and leaderboard submission.

The 'awesome-deliberative-prompting' repository focuses on how to ask Large Language Models (LLMs) to produce reliable reasoning and make reason-responsive decisions through deliberative prompting. It includes success stories, prompting patterns and strategies, multi-agent deliberation, reflection and meta-cognition, text generation techniques, self-correction methods, reasoning analytics, limitations, failures, puzzles, datasets, tools, and other resources related to deliberative prompting. The repository provides a comprehensive overview of research, techniques, and tools for enhancing reasoning capabilities of LLMs.

The Awesome-Neuro-Symbolic-Learning-with-LLM repository is a curated collection of papers and resources focusing on improving reasoning and planning capabilities of Large Language Models (LLMs) and Multi-Modal Large Language Models (MLLMs) through neuro-symbolic learning. It covers a wide range of topics such as neuro-symbolic visual reasoning, program synthesis, logical reasoning, mathematical reasoning, code generation, visual reasoning, geometric reasoning, classical planning, game AI planning, robotic planning, AI agent planning, and more. The repository provides a comprehensive overview of tutorials, workshops, talks, surveys, papers, datasets, and benchmarks related to neuro-symbolic learning with LLMs and MLLMs.

Oat is a simple and efficient framework for running online LLM alignment algorithms. It implements a distributed Actor-Learner-Oracle architecture, with components optimized using state-of-the-art tools. Oat simplifies the experimental pipeline of LLM alignment by serving an Oracle online for preference data labeling and model evaluation. It provides a variety of oracles for simulating feedback and supports verifiable rewards. Oat's modular structure allows for easy inheritance and modification of classes, enabling rapid prototyping and experimentation with new algorithms. The framework implements cutting-edge online algorithms like PPO for math reasoning and various online exploration algorithms.

LlamaV-o1 is a Large Multimodal Model designed for spontaneous reasoning tasks. It outperforms various existing models on multimodal reasoning benchmarks. The project includes a Step-by-Step Visual Reasoning Benchmark, a novel evaluation metric, and a combined Multi-Step Curriculum Learning and Beam Search Approach. The model achieves superior performance in complex multi-step visual reasoning tasks in terms of accuracy and efficiency.

The Awesome-System2-Reasoning-LLM repository is dedicated to a survey paper titled 'From System 1 to System 2: A Survey of Reasoning Large Language Models'. It explores the development of reasoning Large Language Models (LLMs), their foundational technologies, benchmarks, and future directions. The repository provides resources and updates related to the research, tracking the latest developments in the field of reasoning LLMs.

LLM-Synthetic-Data is a repository focused on real-time, fine-grained LLM-Synthetic-Data generation. It includes methods, surveys, and application areas related to synthetic data for language models. The repository covers topics like pre-training, instruction tuning, model collapse, LLM benchmarking, evaluation, and distillation. It also explores application areas such as mathematical reasoning, code generation, text-to-SQL, alignment, reward modeling, long context, weak-to-strong generalization, agent and tool use, vision and language, factuality, federated learning, generative design, and safety.

Awesome LLM Strawberry is a collection of research papers and blogs related to OpenAI Strawberry(o1) and Reasoning. The repository is continuously updated to track the frontier of LLM Reasoning.

PURE (Process-sUpervised Reinforcement lEarning) is a framework that trains a Process Reward Model (PRM) on a dataset and fine-tunes a language model to achieve state-of-the-art mathematical reasoning capabilities. It uses a novel credit assignment method to calculate return and supports multiple reward types. The final model outperforms existing methods with minimal RL data or compute resources, achieving high accuracy on various benchmarks. The tool addresses reward hacking issues and aims to enhance long-range decision-making and reasoning tasks using large language models.

This repository focuses on test-time computing, exploring various strategies such as test-time adaptation, modifying the input, editing the representation, calibrating the output, test-time reasoning, and search strategies. It covers topics like self-supervised test-time training, in-context learning, activation steering, nearest neighbor models, reward modeling, and multimodal reasoning. The repository provides resources including papers and code for researchers and practitioners interested in enhancing the reasoning capabilities of large language models.

AReaL (Ant Reasoning RL) is an open-source reinforcement learning system developed at the RL Lab, Ant Research. It is designed for training Large Reasoning Models (LRMs) in a fully open and inclusive manner. AReaL provides reproducible experiments for 1.5B and 7B LRMs, showcasing its scalability and performance across diverse computational budgets. The system follows an iterative training process to enhance model performance, with a focus on mathematical reasoning tasks. AReaL is equipped to adapt to different computational resource settings, enabling users to easily configure and launch training trials. Future plans include support for advanced models, optimizations for distributed training, and exploring research topics to enhance LRMs' reasoning capabilities.

The Awesome-LLM-Post-training repository is a curated collection of influential papers, code implementations, benchmarks, and resources related to Large Language Models (LLMs) Post-Training Methodologies. It covers various aspects of LLMs, including reasoning, decision-making, reinforcement learning, reward learning, policy optimization, explainability, multimodal agents, benchmarks, tutorials, libraries, and implementations. The repository aims to provide a comprehensive overview and resources for researchers and practitioners interested in advancing LLM technologies.

This repository contains a collection of papers related to tool learning with large language models (LLMs). The papers are organized according to the survey paper 'Tool Learning with Large Language Models: A Survey'. The survey focuses on the benefits and implementation of tool learning with LLMs, covering aspects such as task planning, tool selection, tool calling, response generation, benchmarks, evaluation, challenges, and future directions in the field. It aims to provide a comprehensive understanding of tool learning with LLMs and inspire further exploration in this emerging area.

Awesome LLM plaza is a curated list of awesome LLM papers, projects, and resources. It is updated daily and includes resources from a variety of sources, including huggingface daily papers, twitter, github trending, paper with code, weixin, etc.

XTuner is an efficient, flexible, and full-featured toolkit for fine-tuning large models. It supports various LLMs (InternLM, Mixtral-8x7B, Llama 2, ChatGLM, Qwen, Baichuan, ...), VLMs (LLaVA), and various training algorithms (QLoRA, LoRA, full-parameter fine-tune). XTuner also provides tools for chatting with pretrained / fine-tuned LLMs and deploying fine-tuned LLMs with any other framework, such as LMDeploy.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

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Powered by GPT-4 Turbo. 128,000 Tokens. Knowledge base of Discrete Math concepts, proofs and terminology. This GPT is instructed to carefully read and understand the prompt, plan a strategy to solve the problem, and write formal mathematical proofs.

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MathRelated is an AI-powered tutoring assistant designed for Years 7-12, focusing on bridging learning gaps in mathematics. It offers customized lessons, and interactive problem-solving, enhancing understanding and engagement

Your guide to aligning lesson plans with Common Core standards. Standards checked and updated daily.

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