Best AI tools for< Improve Math Reasoning >

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.

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.

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.

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.

Maths.ai is an AI-powered online math tutor that aims to make learning math cool and engaging. It provides step-by-step explanations to help users master various math topics from arithmetic to calculus. The platform offers personalized learning experiences, 24/7 availability, and access to AI-powered assistance for students worldwide. Maths.ai is designed to help students of all levels improve their math skills in a judgment-free and affordable environment.

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.

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.

Studeo is an AI-powered educational platform that offers personalized learning experiences to students in the field of mathematics. Students can interact with their AI avatar to learn formulas, practice exercises, play games, and take tests. The platform is designed to help students improve their grades by providing feedback, tips, and a dialogue feature with the AI avatar. Studeo covers various academic levels and subjects, making it a comprehensive tool for students seeking to enhance their math skills.

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.

Solvely is an all-in-one AI homework helper that provides step-by-step solutions for all courses, from K12 to Graduate school. It covers a wide range of subjects, from STEM to Liberal Arts, and offers detailed explanations to help users understand complex problems. With a high accuracy rate and a user-friendly interface, Solvely aims to make learning and problem-solving easier for students, parents, and teachers worldwide.

Studyable is an AI-powered platform designed to assist students with homework help and flashcards. The application leverages artificial intelligence technology to provide personalized learning experiences for users. With Studyable, students can access a wide range of study materials, practice questions, and interactive flashcards to enhance their understanding of various subjects. The platform aims to make studying more efficient and engaging by offering tailored recommendations and adaptive learning features. Studyable is a valuable tool for students seeking academic support and looking to improve their study habits.

Gauth is an AI-powered homework helper that provides step-by-step solutions to STEM problems. It utilizes advanced algorithms and AI technology to solve complex math, statistics, calculus, physics, chemistry, biology, and history questions. Gauth also offers live expert support, with thousands of real experts available 24/7 to provide detailed explanations and guidance. The app is designed to help students of all grades and levels conquer challenging homework problems and improve their understanding of STEM subjects.

Quizard AI is an academic assistance tool designed to help students with their studies. It allows users to take a picture of a problem and receive instant answers. The app covers a wide range of subjects and adapts to the format of the questions asked. Quizard also encourages users to ask follow-up questions and provides explanations to help them understand the concepts better.

Synthesis is an innovative educational platform designed for kids who seek to think independently and excel in math and problem-solving. Developed in collaboration with DARPA researchers, it offers a superhuman math tutor and collaborative games to enhance children's problem-solving and communication skills. Founded as part of the SpaceX school initiative, Synthesis aims to cultivate student voice, strategic thinking, and collaborative problem-solving abilities. The platform provides unique learning experiences to a global community, empowering students to develop essential skills for the future.

Tutorly.ai is an AI-powered homework helper that provides step-by-step solutions to math, science, and English problems. It also offers personalized learning recommendations and practice questions to help students improve their understanding of the material. Tutorly.ai is designed to be easy to use, with a simple interface and clear explanations. It is also affordable, with a variety of subscription plans to fit any budget.

Tutory, formerly known as Persona, is an AI-powered educational platform that introduces Dahlia, a conversational AI system designed to tutor students in Math, Science, Computer Science, and English. Dahlia offers personalized support through a user-friendly conversational interface, catering to individual learning styles and needs. The system is open domain, capable of engaging students in 130 languages worldwide, ensuring no student is left behind.

HomeworkAI is an AI-powered homework helper that provides step-by-step solutions to students and educational professionals of all levels. With HomeworkAI, users can upload their homework assignments, practice questions, or type in their questions to receive instant and accurate answers. HomeworkAI covers a wide range of subjects, including mathematics, physics, biology, chemistry, literature, and history. The platform is easy to use and provides clear and concise solutions, making it a valuable tool for students looking to improve their grades and understanding of the subject matter.

AI Does Your Homework is an innovative AI tool designed to assist students with their homework assignments. The tool utilizes advanced artificial intelligence algorithms to provide accurate solutions to a wide range of academic questions and problems. Students can simply input their questions into the tool, and it will generate step-by-step solutions, explanations, and answers in real-time. AI Does Your Homework aims to streamline the learning process, enhance understanding of complex topics, and improve academic performance.

Question AI is a free AI homework helper designed to assist students with their homework assignments. The tool utilizes artificial intelligence to provide accurate and reliable answers to a wide range of academic questions. Students can simply input their homework questions into the tool, and it will generate step-by-step solutions to help them understand the concepts better. With Question AI, students can improve their learning outcomes and enhance their academic performance.

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.

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.

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.

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.

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.

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.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

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.

SeaLLMs are a family of language models optimized for Southeast Asian (SEA) languages. They were pre-trained from Llama-2, on a tailored publicly-available dataset, which comprises texts in Vietnamese 🇻🇳, Indonesian 🇮🇩, Thai 🇹🇭, Malay 🇲🇾, Khmer🇰🇭, Lao🇱🇦, Tagalog🇵🇭 and Burmese🇲🇲. The SeaLLM-chat underwent supervised finetuning (SFT) and specialized self-preferencing DPO using a mix of public instruction data and a small number of queries used by SEA language native speakers in natural settings, which **adapt to the local cultural norms, customs, styles and laws in these areas**. SeaLLM-13b models exhibit superior performance across a wide spectrum of linguistic tasks and assistant-style instruction-following capabilities relative to comparable open-source models. Moreover, they outperform **ChatGPT-3.5** in non-Latin languages, such as Thai, Khmer, Lao, and Burmese.

This repository serves as a comprehensive hub for updates on generative AI research, interview materials, notebooks, and more. It includes monthly best GenAI papers list, interview resources, free courses, and code repositories/notebooks for developing generative AI applications. The repository is regularly updated with the latest additions to keep users informed and engaged in the field of generative AI.

TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. It enables a data & learning flywheel for LLMs by unifying inference, observability, optimization, and experimentation. The platform includes a high-performance model gateway, structured schema-based inference, observability, experimentation, and data warehouse for analytics. TensorZero Recipes optimize prompts and models, and the platform supports experimentation features and GitOps orchestration for deployment.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

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**

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.

This repository is dedicated to collecting and categorizing papers related to Retrieval-Augmented Generation (RAG) for AI-generated content. It serves as a survey repository based on the paper 'Retrieval-Augmented Generation for AI-Generated Content: A Survey'. The repository is continuously updated to keep up with the rapid growth in the field of RAG.

Friendly nudges towards math/logic problems, adjusts to user's level.

Expert math tutor and problem solver with online research and data analysis skills.

Dieses GPT wurde speziell entwickelt, um Schülern beim Verständnis und Lernen mathematischer Konzepte zu helfen. Es bietet einfache Erklärungen, zeigt Beispiele auf und schlägt interaktive Übungen vor, um das Verständnis zu vertiefen.

Child-friendly, fun multiplication times table GPT tutor created by a 9-year-old.

Friendly tutor enhancing mental math for case interviews.

用中文回答所有问题的学术导师

Your personal math coach for mastering GED Math, turning challenges into achievements with engaging, tailored support.

Dit programma biedt duidelijke uitleg over een breed scala aan wiskundige onderwerpen. Gebruikers kunnen verwachten dat ze alles leren, van elementaire wiskundige concepten tot complexere theorieën. Het is ontworpen om wiskunde voor iedereen begrijpelijk te maken.

Soy un tutor interactivo para enseñanza de álgebra, personalizando explicaciones y ejercicios para cada estudiante.

Lively Chinese guide for sequential probability problem-solving.

Taylor Swift-style tutor with visual aids for dyslexia/dyscalculia.

Customized, interactive AI tutor for personalized learning across various subjects and educational levels.

Educational assistant for personalized learning across various topics.

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My goal is to adaptively teach you in the most efficient way possible according to how you learn best. I can teach you virtually anything.

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CBSE school tutor for subjects like Maths, Science, English, and Social Studies.

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Gives you tips and suggestions on how you can improve your application for your users.