Best AI tools for< Improve Student Performance >

mapEDU is an AI-powered curriculum mapping and exam tagging software designed specifically for healthcare professions schools. It uses natural language processing and machine learning to automatically extract relevant MeSH tags from existing digital content, map events/courses/programs with outcomes, and auto-tag exam questions. This provides healthcare professions schools with objective, actionable data to improve curriculum design, validate revisions, and enhance student performance analytics.

Edexia is an AI-powered platform designed to revolutionize the assessment process in education. It offers advanced features such as AI assessment moderation and feedback, aiming to improve all aspects of assessment while saving teachers up to 80% of their time. Edexia focuses on providing better feedback, grading, insights, and efficiency, ultimately transforming the assessment experience for both teachers and students. The platform is trusted by various schools and is committed to positively impacting education by enhancing the teacher-student connection and improving student outcomes.

MacWhisper is a native macOS application that utilizes OpenAI's Whisper technology for transcribing audio files into text. It offers a user-friendly interface for recording, transcribing, and editing audio, making it suitable for various use cases such as transcribing meetings, lectures, interviews, and podcasts. The application is designed to protect user privacy by performing all transcriptions locally on the device, ensuring that no data leaves the user's machine.

FALTAH is an AI-powered Interview Simulation tool designed to help users practice interview questions, enhance their skills, and receive tips for their next interview. The tool utilizes artificial intelligence to provide personalized feedback, performance reports, personality analysis, and CV parsing. It aims to assist students, job seekers, and remote workers in improving their interview skills and increasing their job prospects.

GetSound.ai is an AI-powered deep focus application that helps users minimize distractions and enhance productivity through real-time soundscapes. The app offers a variety of background music and sounds for studying, creating a distraction-free environment for peak performance. With innovative RTS technology, GetSound.AI provides users with unique and constantly varying soundscapes tailored to their environment, including weather-reactive features. Users can immerse themselves in high-quality audio experiences to boost focus, relaxation, and mindfulness. The app is available for desktop platforms and mobile devices, offering a seamless and personalized user experience.

MonitUp is an AI-powered time tracking software that helps you track computer activity, gain insights into work habits, and boost productivity. It uses artificial intelligence to generate personalized suggestions to help you increase productivity and work more efficiently. MonitUp also offers a performance appraisal feature for remote employees, allowing you to evaluate and improve their performance based on objective data.

Scribbr.com is an online platform that offers academic proofreading and editing services for students and academics. The website helps users improve the quality of their academic papers by providing professional editing and feedback. Scribbr.com aims to assist users in enhancing their writing skills and academic performance by offering personalized feedback and suggestions. The platform is designed to support users in achieving their academic goals by providing high-quality editing services and educational resources.

Mantra AI is an AI-powered productivity application designed to help users enhance their daily routines, boost productivity, and improve well-being. It offers a suite of intelligent features such as AI device tracking, personalized playlists, mindfulness assistant, smart task management, focus optimization, and adaptive scheduling. Users can optimize their digital habits, prioritize tasks, minimize distractions, and achieve mental clarity with the help of AI technology. Mantra AI aims to revolutionize workflow, enhance focus, and provide personalized recommendations for a harmonious and productive day.

The SAT Reading & Writing Question Generator is an AI-powered tool designed to help students practice for the SAT exam. It generates a wide variety of reading and writing questions to improve students' skills and boost their confidence. With its smart algorithms, the tool provides personalized practice questions tailored to each student's needs, making exam preparation more effective and efficient. The tool is user-friendly and accessible, offering a seamless experience for students to enhance their test-taking abilities.

Gizmo is an AI-powered learning application designed to make studying easy and enjoyable for students of all levels. It offers A.I. quizzes that help users learn and retain information effectively. The app is created by Cambridge alumni and has gained popularity among students for its innovative approach to learning. With features like spaced repetition, active recall, and the ability to turn study materials into flashcards, Gizmo aims to enhance the learning experience and improve academic performance.

StudyPro is a premier online learning platform designed for students to enhance their academic performance. It offers a wide range of services, including grammar checking, paraphrasing, homework planning, and AI writing tools. StudyPro leverages advanced AI technologies to provide personalized learning experiences and support students in achieving their educational goals. The platform aims to simplify the learning process by offering innovative features and top-notch support to help students succeed in their academic journey.

Learning Copilot is an AI-powered platform designed to assist users in enhancing their learning experience. It leverages artificial intelligence to provide personalized recommendations, interactive study materials, and real-time feedback to help users improve their knowledge retention and academic performance. With a user-friendly interface and advanced algorithms, Learning Copilot aims to revolutionize the way people learn by making education more engaging, efficient, and effective.

Akadimia Ai is an AI-powered platform designed to provide users with a range of educational resources and tools. The platform leverages artificial intelligence to offer personalized learning experiences, interactive tutorials, and assessments. Users can access a variety of courses, quizzes, and study materials tailored to their individual needs and learning preferences. Akadimia Ai aims to enhance the learning process by offering adaptive content recommendations and progress tracking features. Whether you are a student looking to improve your academic performance or a professional seeking to acquire new skills, Akadimia Ai offers a comprehensive learning solution to help you achieve your goals.

Infinipilot.AI is an AI co-pilot application designed for macOS users to enhance productivity and streamline various tasks. It offers features such as autocomplete, style and grammar fixes, translation, developer utilities, and AI-driven question answering. The application prioritizes privacy by using local language models and provides accessibility features like text-to-speech and speech-to-text functionalities. Infinipilot.AI integrates with various AI models like OpenAI and Claude, ensuring efficient performance and continuous updates. The application also offers discounts for students and non-profit organizations, along with a 14-day money-back guarantee.

Open Tutor App is an AI-powered Homework Helper designed to assist students in solving homework questions efficiently. The app allows users to take a photo of their homework, which is then analyzed by AI to provide step-by-step solutions and explanations. With features like scanning and solving homework questions, Open Tutor App aims to enhance learning experiences and boost academic performance. The application is available for download on Google Play, App Store, and Web platforms.

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.

Learnrithm is an AI-powered learning platform designed to make learning easier and more accessible. It offers personalized learning paths, interactive quizzes, certification upon course completion, 24/7 accessibility, diverse learning resources, and expert instructors. With features like AI Quiz Generator, Ai Teacher, and Chat With PDF, Learnrithm aims to provide a comprehensive solution for students and teachers to enhance their learning experience. Trusted by students from over 1000 universities worldwide, Learnrithm has proven to be a valuable tool in improving academic performance and understanding of study materials.

AI Humanizer is a free online tool that utilizes advanced algorithms to imitate human writing. It helps users convert AI-generated text into content that appears to be written by a human. The tool offers features like natural language processing, contextual understanding, SEO optimization, and plagiarism detection avoidance. It is beneficial for content creators, marketers, students, and businesses looking to enhance their writing and SEO performance.

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.

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**

Cherry Data Selection project introduces a self-guided methodology for LLMs to autonomously discern and select cherry samples from open-source datasets, minimizing manual curation and cost for instruction tuning. The project focuses on selecting impactful training samples ('cherry data') to enhance LLM instruction tuning by estimating instruction-following difficulty. The method involves phases like 'Learning from Brief Experience', 'Evaluating Based on Experience', and 'Retraining from Self-Guided Experience' to improve LLM performance.

llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.

DistillKit is an open-source research effort by Arcee.AI focusing on model distillation methods for Large Language Models (LLMs). It provides tools for improving model performance and efficiency through logit-based and hidden states-based distillation methods. The tool supports supervised fine-tuning and aims to enhance the adoption of open-source LLM distillation techniques.

The repository 'Awesome-LLM-Preference-Learning' is the official repository of a survey paper titled 'Towards a Unified View of Preference Learning for Large Language Models: A Survey'. It contains a curated list of papers related to preference learning for Large Language Models (LLMs). The repository covers various aspects of preference learning, including on-policy and off-policy methods, feedback mechanisms, reward models, algorithms, evaluation techniques, and more. The papers included in the repository explore different approaches to aligning LLMs with human preferences, improving mathematical reasoning in LLMs, enhancing code generation, and optimizing language model performance.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

Reflection-Tuning is a project focused on improving the quality of instruction-tuning data through a reflection-based method. It introduces Selective Reflection-Tuning, where the student model can decide whether to accept the improvements made by the teacher model. The project aims to generate high-quality instruction-response pairs by defining specific criteria for the oracle model to follow and respond to. It also evaluates the efficacy and relevance of instruction-response pairs using the r-IFD metric. The project provides code for reflection and selection processes, along with data and model weights for both V1 and V2 methods.

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.

Awesome LLM for APR is a repository dedicated to exploring the capabilities of Large Language Models (LLMs) in Automated Program Repair (APR). It provides a comprehensive collection of research papers, tools, and resources related to using LLMs for various scenarios such as repairing semantic bugs, security vulnerabilities, syntax errors, programming problems, static warnings, self-debugging, type errors, web UI tests, smart contracts, hardware bugs, performance bugs, API misuses, crash bugs, test case repairs, formal proofs, GitHub issues, code reviews, motion planners, human studies, and patch correctness assessments. The repository serves as a valuable reference for researchers and practitioners interested in leveraging LLMs for automated program repair.

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

This repository is a curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their variants. It includes tutorials, papers, tools, frameworks, and best practices to aid researchers, data scientists, and machine learning practitioners in adapting pre-trained models to specific tasks and domains. The resources cover a wide range of topics related to fine-tuning LLMs, providing valuable insights and guidelines to streamline the process and enhance model performance.

ChatGPT Queue Prompts is a collection of prompt chains designed to enhance interactions with large language models like ChatGPT. These prompt chains help build context for the AI before performing specific tasks, improving performance. Users can copy and paste prompt chains into the ChatGPT Queue extension to process prompts in sequence. The repository includes example prompt chains for tasks like conducting AI company research, building SEO optimized blog posts, creating courses, revising resumes, enriching leads for CRM, personal finance document creation, workout and nutrition plans, marketing plans, and more.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

Obsidian Weaver is a plugin that integrates ChatGPT/GPT-3 into the note-taking workflow of Obsidian. It allows users to easily access AI-generated suggestions and insights within Obsidian, enhancing the writing and brainstorming process. The plugin respects Obsidian's philosophy of storing notes locally, ensuring data security and privacy. Weaver offers features like creating new chat sessions with the AI assistant and receiving instant responses, all within the Obsidian environment. It provides a seamless integration with Obsidian's interface, making the writing process efficient and helping users stay focused. The plugin is constantly being improved with new features and updates to enhance the note-taking experience.

A comprehensive repository focusing on 'Model Merging in LLMs, MLLMs, and Beyond', providing an exhaustive overview of model merging methods, theories, applications, and future research directions. The repository covers various advanced methods, applications in foundation models, different machine learning subfields, and tasks like pre-merging methods, architecture transformation, weight alignment, basic merging methods, and more.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

This repository aims to promote global equality for individuals pursuing a PhD in NLP by providing resources and information on various aspects of the academic journey. It covers topics such as applying for a PhD, getting research opportunities, preparing for the job market, and succeeding in academia. The repository is actively updated and includes contributions from experts in the field.

EvoMaster is an open-source AI-driven tool that automatically generates system-level test cases for web/enterprise applications. It uses Evolutionary Algorithm and Dynamic Program Analysis to evolve test cases, maximizing code coverage and fault detection. It supports REST, GraphQL, and RPC APIs, with whitebox testing for JVM-compiled APIs. The tool generates JUnit tests in Java or Kotlin, focusing on fault detection, self-contained tests, SQL handling, and authentication. Known limitations include manual driver creation for whitebox testing and longer execution times for better results. EvoMaster has been funded by ERC and RCN grants.

💃📘🕺 Master College Dance Performance with AI! 🎭📚 This tool offers expert answers, choreography tips, and insights into various dance styles. 🎶👯‍♀️ Ideal for students perfecting their art and stage presence. 🩰🎓

A medical residency interview coach providing questions and feedback.

Versatile coach for diverse advice in academics, business, art, and more.

I'm like a test taker, answering questions across various subjects.

Versatile blog blending assistant, excels in creative mixing.

Aide for educators writing K-12 progress report comments.

GPT especializado en generar rúbricas de evaluación educativas

School Advisory with Enhanced Dataset Analysis

Offers exercises and techniques to improve memory retention and cognitive functions.

A simple way to build your CV from scratch or improve existing one

Guides in structuring essays to improve writing skills, adapting to skill levels.

GPT-powered essay rewriter designed to rephrase, enhance, and improve existing essays while maintaining the original meaning, tailored to specific instructions regarding style, tone, and desired improvements.

Expert AI Doctor with up to date medical resources and textbooks to help improve your clinical skills.

使用GPTS快速识别关键因素，提高决策效率和工作效率，找到关键的20%，Use GPTS to quickly identify key factors, improve decision-making efficiency and work efficiency, and find the key 20%.

A moot competition companion. & Trial Prep companion . Test and improve arguments- predict your opponent's reaction.

メールの作成・添削・返信の提案などを行います。メールの校正は、草案をそのままコピペするだけで可能です。件名・署名・添付ファイルなどを忘れないようリマインドも行います。さらにこのGPTは、特別な設定で「Use conversation data in your GPT to improve our models」の項目をOFFにしています。そのため、うっかり機密情報が含まれるメール文を送信してしまった場合でも、ChatGPTの学習に利用されないと思われます。 ※ただし、今後の仕様変更や他の経路からの情報漏洩などのリスクもありえます。個人情報は決して書き込まないでください。

Explores attention in cognition and offers focus improvement tips.

Analyzes essays for similarities, offers scores and writing tips.

A mentor who provides detailed feedback on student work.