Best AI tools for< Study Collaboratively >

PrepSup is an AI-powered platform that offers a combination of powerful flashcards, AI tutoring, and PDF analysis tools. It provides a comprehensive solution for students and professionals to enhance their learning experience, improve retention, and analyze PDF documents efficiently. With PrepSup, users can create interactive flashcards, receive personalized tutoring based on AI algorithms, and analyze PDF files for key information. The platform aims to streamline the learning process and make studying more effective and engaging.

LearnMate is a revolutionary AI-integrated productivity app designed for students. It offers collaborative tools for study goal setting, assignment and task management, note-taking, and more. The app utilizes cutting-edge AI technology to enhance the learning experience and productivity of students. LearnMate is accessible on various devices, allowing seamless progress tracking and data synchronization across PCs, tablets, and mobile devices. With features like AI tutor assistance, assignment management, task lists, study notes creation, and more, LearnMate aims to revolutionize the way students study and excel in their academic endeavors.

StudyNinja is an AI-enhanced study buddy designed to revolutionize the academic journey of students. It offers a holistic productivity solution by blending smart task management, interactive study tools, and a unique AI Tutor. StudyNinja fosters active learning, efficient organization, and effective time management to enhance academic performance. The application provides features such as personalized study goals, assignment management, task management, study notes, and collaborative assignments. It is a cloud-based productivity software that works seamlessly on PC, tablet, or mobile devices, offering ultimate flexibility and hassle-free learning experience.

Buildalesson is an AI-powered educational platform that revolutionizes traditional study sessions by offering interactive and engaging learning experiences. It provides educators, students, and parents with tools to create lessons, quizzes, and interactive video lessons effortlessly. With AI-generated questions and interventions, Buildalesson enhances comprehension, fosters engagement, and transforms the learning process. The platform aims to make learning exciting, effective, and collaborative, catering to a wide range of users in the education sector.

Tube Memo is an AI-powered tool designed to facilitate effortless note-taking from YouTube videos. It allows users to capture transcripts, organize notes, and generate summaries from videos. The tool enhances productivity by providing features like timestamped transcripts, AI-powered summaries, content organizing, and the ability to easily share and download notes. Users can collaborate with team members, categorize and tag memos for efficient searching, and access their notes across various devices. Tube Memo aims to streamline the process of extracting key insights from video content, making it a valuable asset for students, professionals, content creators, and researchers.

Sumazon is an AI-powered educational platform that simplifies learning through document and video summarization, practice exams, true/false quizzes, and flashcards. It offers powerful features such as summarizing documents and videos, creating study sets, collaborative learning, and multilingual support. With advanced AI capabilities and 24/7 customer support, Sumazon aims to make education more accessible, engaging, and effective for students worldwide.

StudyShift is a revolutionary collaborative productivity tool specifically designed for students. It is made to make students more efficient and productive. It works everywhere, whether on a PC, tablet, or mobile device. With StudyShift, students can set their study goals and track their progress efficiently. They can also manage their assignments, create documents, collaborate with others, and manage their tasks. StudyShift also includes an AI tutor that can answer questions on any subject. It is a revolutionary suite of productivity tools and apps for learners that works everywhere, whether on a PC, tablet, or mobile device.

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.

StudyFetch is a revolutionary new platform that allows you to upload your course materials and create interactive study sets. You can study with an AI tutor, create flashcards, generate notes, take practice tests, and more. StudyFetch's AI, Spark.e, utilizes advanced machine learning algorithms to offer a tailored, interactive tutoring experience. Once you upload your study materials, Spark.e scans and indexes them, making the content searchable and accessible for real-time queries.

Study Plannr is an AI-powered application that generates personalized and smart study plans using ChatGPT. It optimizes revision by considering subjects, topics, and assessment dates. The tool is designed to help parents, educators, K12 students, and learners studying for certifications in creating customized study plans to improve learning efficiency and goal setting.

Interview.study is an AI-powered interview preparation platform that helps candidates practice real interview questions asked by top companies. The platform provides users with instant feedback on their responses, helping them identify areas for improvement and develop stronger answers. Interview.study also offers a variety of features to help candidates prepare for their interviews, including a database of interview questions, a mock interview tool, and a resume builder.

Hebrew Bible Study is a website dedicated to providing resources for studying the Hebrew Bible. Users can access various features such as unlocking pro features, asking Rabbi Ari questions, and customizing their study plans. The website is designed to help users deepen their understanding of Judaism through the study of the Hebrew Bible. It is created by Cohen Apps and based in Jerusalem.

Sara is an AI-powered platform that serves as a virtual tutor and exam planner. It leverages artificial intelligence to provide personalized learning experiences and help students prepare for exams efficiently. With Sara, users can access study materials, receive customized study plans, track their progress, and get feedback on their performance. The platform aims to enhance learning outcomes by offering adaptive learning solutions tailored to individual needs.

Course Hero is an online learning platform that provides students with access to a library of study materials, including textbooks, lecture notes, practice questions, and expert help. The platform uses AI to power its search engine and provide personalized recommendations to students. Course Hero also offers a subscription service that gives students access to additional features, such as the ability to download documents and get help from live tutors.

Quizgecko is an AI-powered platform that helps users create quizzes, flashcards, and assessments from existing content. It utilizes AI technology to generate questions and answers, offers spaced repetition for optimized learning, provides personalized feedback through an AI tutor, and allows users to study smarter with a mobile app. The platform is suitable for students, educators, and businesses looking to enhance learning and evaluation processes.

Memo is an AI-powered tool designed to transform course materials into instant notes, flashcards, and quizzes in seconds. It automates flashcard creation, offers personalized learning experiences, and saves valuable study time. Trusted by educators and learners worldwide, Memo covers 24 diverse disciplines and supports over 100 languages. The tool is built by medical students to streamline the study process, enhance learning experiences, and improve study efficiency.

OmniSets is an ultimate flashcard tool that helps students learn efficiently. It combines advanced machine learning algorithms and incorporates them throughout the platform. OmniSets offers various modes, from spaced repetition to matching games and AI tools, to make studying easier. Users can create and organize study sets, search from over 250k+ public study sets, and take advantage of the spell tool to write terms and definitions. OmniSets is a community-driven platform that values user feedback and is constantly updating and improving its features.

KardsAI is an AI-powered flashcard maker application that aims to make learning easier and more efficient. It allows users to transform any PDF, text, note, or prompt into flashcards in a snap. With features like converting PDFs to flashcards, generating flashcards from prompts, and cross-platform access, KardsAI caters to students, language learners, knowledge seekers, and trivia enthusiasts. The application saves valuable time through AI-powered flashcard creation and helps users remember information longer with a spaced repetition algorithm. KardsAI offers a freemium model, allowing users to use the app for free or upgrade for additional features at an affordable price.

KardsAI is an AI-powered flashcard maker mobile app designed to help users study smarter and more efficiently. It allows users to transform any PDF, text, note, or prompt into flashcards in a snap. With advanced AI features and a mobile-first approach, KardsAI offers exceptional quality and unique features for personalized learning experiences. The app saves valuable time by automating flashcard creation and incorporates a spaced repetition algorithm to help users remember information longer. KardsAI is suitable for students, language learners, knowledge seekers, and trivia enthusiasts, offering a wide range of functionalities to enhance learning and memory retention.

Synaptiq Learning is an AI-powered learning platform designed for medicine students to study efficiently and effectively. It offers trustworthy, publisher-grade content such as flashcards, practice tests, and free-response questions sourced from reliable medical education materials. The platform utilizes cutting-edge algorithms like spaced repetition to optimize personalized review schedules. Synaptiq is trusted in academia and aims to enhance the learning experience by considering the science behind learning processes.

This repository contains a curated list of resources on generative information retrieval, including research papers, datasets, tools, and applications. Generative information retrieval is a subfield of information retrieval that uses generative models to generate new documents or passages of text that are relevant to a given query. This can be useful for a variety of tasks, such as question answering, summarization, and document generation. The resources in this repository are intended to help researchers and practitioners stay up-to-date on the latest advances in generative information retrieval.

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 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.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

AI Hospital is a research repository focusing on the interactive evaluation and collaboration of Large Language Models (LLMs) as intern doctors for clinical diagnosis. The repository includes a simulation module tailored for various medical roles, introduces the Multi-View Medical Evaluation (MVME) Benchmark, provides dialog history documents of LLMs, replication instructions, performance evaluation, and guidance for creating intern doctor agents. The collaborative diagnosis with LLMs emphasizes dispute resolution. The study was authored by Zhihao Fan, Jialong Tang, Wei Chen, Siyuan Wang, Zhongyu Wei, Jun Xie, Fei Huang, and Jingren Zhou.

Recommenders is a project under the Linux Foundation of AI and Data that assists researchers, developers, and enthusiasts in prototyping, experimenting with, and bringing to production a range of classic and state-of-the-art recommendation systems. The repository contains examples and best practices for building recommendation systems, provided as Jupyter notebooks. It covers tasks such as preparing data, building models using various recommendation algorithms, evaluating algorithms, tuning hyperparameters, and operationalizing models in a production environment on Azure. The project provides utilities to support common tasks like loading datasets, evaluating model outputs, and splitting training/test data. It includes implementations of state-of-the-art algorithms for self-study and customization in applications.

The W3C Cognitive AI Community Group focuses on advancing Cognitive AI through collaboration on defining use cases, open source implementations, and application areas. The group aims to demonstrate the potential of Cognitive AI in various domains such as customer services, healthcare, cybersecurity, online learning, autonomous vehicles, manufacturing, and web search. They work on formal specifications for chunk data and rules, plausible knowledge notation, and neural networks for human-like AI. The group positions Cognitive AI as a combination of symbolic and statistical approaches inspired by human thought processes. They address research challenges including mimicry, emotional intelligence, natural language processing, and common sense reasoning. The long-term goal is to develop cognitive agents that are knowledgeable, creative, collaborative, empathic, and multilingual, capable of continual learning and self-awareness.

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.

The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.

Awesome-Attention-Heads is a platform providing the latest research on Attention Heads, focusing on enhancing understanding of Transformer structure for model interpretability. It explores attention mechanisms for behavior, inference, and analysis, alongside feed-forward networks for knowledge storage. The repository aims to support researchers studying LLM interpretability and hallucination by offering cutting-edge information on Attention Head Mining.

Paper-Reading-ConvAI is a repository that contains a list of papers, datasets, and resources related to Conversational AI, mainly encompassing dialogue systems and natural language generation. This repository is constantly updating.

STORM is a LLM system that writes Wikipedia-like articles from scratch based on Internet search. While the system cannot produce publication-ready articles that often require a significant number of edits, experienced Wikipedia editors have found it helpful in their pre-writing stage. **Try out our [live research preview](https://storm.genie.stanford.edu/) to see how STORM can help your knowledge exploration journey and please provide feedback to help us improve the system 🙏!**

Welcome to the ultimate hub for on-device Large Language Models (LLMs)! This repository is your go-to resource for all things related to LLMs designed for on-device deployment. Whether you're a seasoned researcher, an innovative developer, or an enthusiastic learner, this comprehensive collection of cutting-edge knowledge is your gateway to understanding, leveraging, and contributing to the exciting world of on-device LLMs.

This paper list is about Large Language Model-enhanced Recommender System. It also contains some related works. Keywords: recommendation system, large language models

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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