Best AI tools for< Organize Research >

Lateral is an AI-powered research tool that helps academics and students streamline their workflow by seamlessly searching, saving, and organizing findings across their papers. It uses AI to generate an auto-generated table, name concepts, and provide super search capabilities, making it easy to find relevant information quickly. Lateral also allows users to collaborate and share their work, making it a valuable tool for researchers working on collaborative projects.

Paper Pilot is the ultimate AI tool for concise research paper summaries, key insights, and audio guides. It uses cutting-edge AI to enhance research by providing quick, precise summaries of research papers, organizing research boards, and offering an interactive chat for AI-specific questions. Trusted by top researchers, Paper Pilot simplifies and accelerates the study process, saving valuable time and effort.

OpenRead is an AI-powered research tool that helps users discover, understand, and organize scientific literature. It offers a variety of features to make research more efficient and effective, including semantic search, AI summarization, and note-taking tools. OpenRead is designed to help researchers of all levels, from students to experienced professionals, save time and improve their research outcomes.

AcademicID is an AI-powered platform that helps students and researchers discover and access academic resources. It provides a comprehensive database of academic papers, journals, and other resources, as well as tools to help users organize and manage their research. AcademicID also offers a variety of features to help users collaborate with others and share their research findings.

Focal is an AI-powered tool that helps users summarize and organize their research and reading materials. It offers features such as AI-generated summaries, document highlighting, and collaboration tools. Focal is designed for researchers, students, professionals, and anyone who needs to efficiently process large amounts of information.

Connected Papers is a search engine for academic papers that uses artificial intelligence to help users find and explore relevant research. It allows users to search for papers by keyword, author, or title, and then explore the connections between them. Connected Papers also provides a variety of tools to help users organize and manage their research, including the ability to create custom collections of papers, add notes and annotations, and share their research with others.

CogPrints is an electronic archive for self-archived papers in any area of Psychology, Neuroscience, and Linguistics, and many areas of Computer Science (e.g., artificial intelligence, robotics, vision, learning, speech, neural networks), Philosophy (e.g., mind, language, knowledge, science, logic), Biology (e.g., ethology, behavioral ecology, sociobiology, behavior genetics, evolutionary theory), Medicine (e.g., Psychiatry, Neurology, human genetics, Imaging), Anthropology (e.g., primatology, cognitive ethnology, archeology, paleontology), as well as any other portions of the physical, social and mathematical sciences that are pertinent to the study of cognition.

Recall is a web and mobile application that allows users to summarize and save any online content. It uses artificial intelligence to automatically categorize and connect saved content, making it easy to find and rediscover later. Recall also offers spaced repetition learning, data export, and offline access.

ConceptMap.AI is a free concept map maker designed for knowledge workers to shape their ideas into clear, professional concept maps instantly. Users can create concept maps by chatting with AI, allowing them to visualize their thoughts in seconds. The application is ideal for education, project planning, brainstorming, content creation, process mapping, and research purposes. With AI-powered diagramming, real-time collaboration, an extensive template library, and export capabilities, ConceptMap.AI offers a user-friendly experience for creating and sharing visual maps.

DiscoveryAi is an AI-powered research assistant that helps you find and organize the information you need to make better decisions. With DiscoveryAi, you can quickly and easily search through a vast database of articles, news, and other content to find the information you need. You can also use DiscoveryAi to organize your research into folders and notes, and to collaborate with others on research projects.

PaperClip is an AI tool designed to help users keep track of their daily AI papers review. It allows users to memorize details from papers in machine learning, computer vision, and natural language processing. The tool provides an extension that enables users to find back important findings from AI research papers, ML blog posts, and news. PaperClip's AI runs locally, ensuring data privacy by not sending any information to external servers. With features like offline support, data cleaning, and easy reset options, PaperClip offers a convenient solution for organizing and accessing research findings.

ResearchRabbit is a research tool that helps researchers discover and organize academic papers. It uses artificial intelligence to recommend papers that are relevant to a researcher's interests and to visualize networks of papers and co-authorships. ResearchRabbit also allows researchers to collaborate on collections of papers and to share their findings with others.

moyoNote is an AI-powered tool designed for organizing, managing, and structuring information into a comprehensive knowledge base. It offers features such as generating mind maps from text or files, interactive Q&A for maps, and customization options for personal expression. Users can easily share mind maps with others and control access permissions. The tool aims to simplify workflow, improve work efficiency, and enhance collaboration among users.

Note Rack is an AI-powered tool designed to help students organize their academic life efficiently. It serves as a centralized platform for managing notes and tasks, enabling users to streamline their study routines. With features like collaboration, sharing, powerful search function, and ChatGPT integration, Note Rack aims to enhance the note-taking experience and provide personalized study assistance. Say goodbye to endless scrolling through handwritten notes and hello to a more productive and effective way of studying.

The website offers a service where users can send their notes to be organized in Notion. Users can get started with Telegram and Slack integration is coming soon. The platform aims to simplify the process of organizing notes and tasks for better productivity.

Emdash is an AI-powered tool designed to help users organize their book highlights efficiently. By utilizing AI technology, Emdash can analyze text snippets, enabling users to remember and learn from their readings effectively. The tool offers features such as conceptual cousins, instant semantic search, tagging, rating, note-taking, and reflection capabilities. Emdash is free, open-source, and allows users to export their organized data back to epub format for review on e-readers. Additionally, the tool promotes random discovery of forgotten ideas, rephrasing dense concepts with metaphors, and supports importing highlights from various sources. Emdash prioritizes user privacy by conducting on-device analysis and offers upcoming features like Monk-Mode Lenses and Socratic switch.

Keepi is a personal knowledge AI application designed to help users capture, organize, and retrieve their knowledge effortlessly. With Keepi, users can capture ideas, documents, and images, and the application uses AI to enrich and organize this knowledge for easy access. Users can leverage their personal knowledge on the go or in the office, making it a valuable tool for enhancing productivity and efficiency. Keepi also offers features such as insights creation, voice message transcription, and drawing capabilities, providing a comprehensive solution for managing and utilizing personal knowledge.

Dokkio is an AI-powered platform that helps users find, organize, and understand all of their online files. By leveraging AI technology, Dokkio enables users to work with their cloud files efficiently and collaboratively. The platform offers tools for managing multiple activities, finding documents and files, compiling research materials, and organizing a content library. Dokkio aims to streamline the process of accessing and utilizing online content, regardless of where it is stored.

Phew AI Tab is an AI-powered tab management tool that helps users organize and retrieve tab information efficiently. It utilizes AI-based grouping and spaces in a vertical sidebar to streamline tab management. With features like AI Grouping & Auto Collapse, AI Analyzing, AI Search, and AI-based Space & Cloud Sync, Phew AI Tab aims to enhance productivity and user experience. The tool ensures privacy with military-grade protection and offers seamless synchronization across devices.

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.

Crawl4AI is a powerful and free web crawling service that extracts valuable data from websites and provides LLM-friendly output formats. It supports crawling multiple URLs simultaneously, replaces media tags with ALT, and is completely free to use and open-source. Users can integrate Crawl4AI into Python projects as a library or run it as a standalone local server. The tool allows users to crawl and extract data from specified URLs using different providers and models, with options to include raw HTML content, force fresh crawls, and extract meaningful text blocks. Configuration settings can be adjusted in the `crawler/config.py` file to customize providers, API keys, chunk processing, and word thresholds. Contributions to Crawl4AI are welcome from the open-source community to enhance its value for AI enthusiasts and developers.

A curated list of Generative AI projects, tools, artworks, and models

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.

The 'Awesome LLMs Planning Reasoning' repository is a curated collection focusing on exploring the capabilities of Large Language Models (LLMs) in planning and reasoning tasks. It includes research papers, code repositories, and benchmarks that delve into innovative techniques, reasoning limitations, and standardized evaluations related to LLMs' performance in complex cognitive tasks. The repository serves as a comprehensive resource for researchers, developers, and enthusiasts interested in understanding the advancements and challenges in leveraging LLMs for planning and reasoning in real-world scenarios.

The Second Brain AI Agent Project is a tool designed to empower personal knowledge management by automatically indexing markdown files and links, providing a smart search engine powered by OpenAI, integrating seamlessly with different note-taking methods, and enhancing productivity by accessing information efficiently. The system is built on LangChain framework and ChromaDB vector store, utilizing a pipeline to process markdown files and extract text and links for indexing. It employs a Retrieval-augmented generation (RAG) process to provide context for asking questions to the large language model. The tool is beneficial for professionals, students, researchers, and creatives looking to streamline workflows, improve study sessions, delve deep into research, and organize thoughts and ideas effortlessly.

This repository provides a systematic and comprehensive review of efficient LLMs research. We organize the literature in a taxonomy consisting of three main categories, covering distinct yet interconnected efficient LLMs topics from **model-centric** , **data-centric** , and **framework-centric** perspective, respectively. We hope our survey and this GitHub repository can serve as valuable resources to help researchers and practitioners gain a systematic understanding of the research developments in efficient LLMs and inspire them to contribute to this important and exciting field.

This repository contains frontier research on explainable AI (XAI), a hot topic in the field of artificial intelligence. It includes trends, use cases, survey papers, books, open courses, papers, and Python libraries related to XAI. The repository aims to organize and categorize publications on XAI, provide evaluation methods, and list various Python libraries for explainable AI.

GPT-All-Star is an AI-powered code generation tool designed for scratch development of web applications with team collaboration of autonomous AI agents. The primary focus of this research project is to explore the potential of autonomous AI agents in software development. Users can organize their team, choose leaders for each step, create action plans, and work together to complete tasks. The tool supports various endpoints like OpenAI, Azure, and Anthropic, and provides functionalities for project management, code generation, and team collaboration.

Emerging Trajectories is an open source library for tracking and saving forecasts of political, economic, and social events. It provides a way to organize and store forecasts, as well as track their accuracy over time. This can be useful for researchers, analysts, and anyone else who wants to keep track of their predictions.

The Artificial Intelligence Incident Database (AIID) is a collection of incidents involving the development and use of artificial intelligence (AI). The database is designed to help researchers, policymakers, and the public understand the potential risks and benefits of AI, and to inform the development of policies and practices to mitigate the risks and promote the benefits of AI. The AIID is a collaborative project involving researchers from the University of California, Berkeley, the University of Washington, and the University of Toronto.

Awesome-Colorful-LLM is a meticulously assembled anthology of vibrant multimodal research focusing on advancements propelled by large language models (LLMs) in domains such as Vision, Audio, Agent, Robotics, and Fundamental Sciences like Mathematics. The repository contains curated collections of works, datasets, benchmarks, projects, and tools related to LLMs and multimodal learning. It serves as a comprehensive resource for researchers and practitioners interested in exploring the intersection of language models and various modalities for tasks like image understanding, video pretraining, 3D modeling, document understanding, audio analysis, agent learning, robotic applications, and mathematical research.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and includes a process of embedding docs, queries, searching for top passages, creating summaries, using an LLM to re-score and select relevant summaries, putting summaries into prompt, and generating answers. The tool can be used to answer specific questions related to scientific research by leveraging citations and relevant passages from documents.

Ichigo is a local real-time voice AI tool that uses an early fusion technique to extend a text-based LLM to have native 'listening' ability. It is an open research experiment with improved multiturn capabilities and the ability to refuse processing inaudible queries. The tool is designed for open data, open weight, on-device Siri-like functionality, inspired by Meta's Chameleon paper. Ichigo offers a web UI demo and Gradio web UI for users to interact with the tool. It has achieved enhanced MMLU scores, stronger context handling, advanced noise management, and improved multi-turn capabilities for a robust user experience.

Neptune is a scalable experiment tracker for teams training foundation models. Log millions of runs, effortlessly monitor and visualize model training, and deploy on your infrastructure. Track 100% of metadata to accelerate AI breakthroughs. Log and display any framework and metadata type from any ML pipeline. Organize experiments with nested structures and custom dashboards. Compare results, visualize training, and optimize models quicker. Version models, review stages, and access production-ready models. Share results, manage users, and projects. Integrate with 25+ frameworks. Trusted by great companies to improve workflow.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

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 🙏!**

AI-TOD is a dataset for tiny object detection in aerial images, containing 700,621 object instances across 28,036 images. Objects in AI-TOD are smaller with a mean size of 12.8 pixels compared to other aerial image datasets. To use AI-TOD, download xView training set and AI-TOD_wo_xview, then generate the complete dataset using the provided synthesis tool. The dataset is publicly available for academic and research purposes under CC BY-NC-SA 4.0 license.

HippoRAG is a novel retrieval augmented generation (RAG) framework inspired by the neurobiology of human long-term memory that enables Large Language Models (LLMs) to continuously integrate knowledge across external documents. It provides RAG systems with capabilities that usually require a costly and high-latency iterative LLM pipeline for only a fraction of the computational cost. The tool facilitates setting up retrieval corpus, indexing, and retrieval processes for LLMs, offering flexibility in choosing different online LLM APIs or offline LLM deployments through LangChain integration. Users can run retrieval on pre-defined queries or integrate directly with the HippoRAG API. The tool also supports reproducibility of experiments and provides data, baselines, and hyperparameter tuning scripts for research purposes.

Fueling-Ambitions-Via-Book-Discoveries is an Advanced Machine Learning & AI Course designed for students, professionals, and AI researchers. The course integrates rigorous theoretical foundations with practical coding exercises, ensuring learners develop a deep understanding of AI algorithms and their applications in finance, healthcare, robotics, NLP, cybersecurity, and more. Inspired by MIT, Stanford, and Harvard’s AI programs, it combines academic research rigor with industry-standard practices used by AI engineers at companies like Google, OpenAI, Facebook AI, DeepMind, and Tesla. Learners can learn 50+ AI techniques from top Machine Learning & Deep Learning books, code from scratch with real-world datasets, projects, and case studies, and focus on ML Engineering & AI Deployment using Django & Streamlit. The course also offers industry-relevant projects to build a strong AI portfolio.

Easy Speedy Wikipedia Citations

Converts book and news URLs to BibTeX

简洁懒人化Markdown笔记助手

私はあなたのインプット情報を全て構造化データとしてマインドマップ化します。あなたがマインドマップ化したい情報をそのまま直接入力してください！

Write what you'd like researched. Get information in a table format.

Connect and interact with your Google accounts. Organize, retrieve, and manipulate data with A.I

Solve math and logic with Smart GPT. Use Tree and Chain of thoughts to organize and find answers.

Assistant to help researchers with thesis research and documentation process.

Comprehensive categorization and organization for AI Prompts

👉在对话框中粘贴笔记内容或上传笔记文件，我将帮助你理清逻辑脉络！✅ 加微信 douge985，🎁 拉你进群领福利

Coaches on Second Brain & PARA, focuses on information categorization.

Experto en organizar información en formato de texto combinado.

Engaging, friendly guide for academic literature reviews using research question or topic

Organizes text into structured output and creates visual mind maps.

Expert in Tiago Forte's Second Brain methodology for digital organization.

Supercharge your personal knowledge management journey by using a highlight capturing service (such as Readwise) and then turning those highlights into useful knowledge assets. Examples include flash cards, research abstracts or articles based off the highlights you collect and choose to combine.

NeuroNote GPT is a specialized AI assistant designed for organizing and summarizing academic articles on neurology and epilepsy, specifically tailored for integration with Obsidian.

你可以投喂自己的考研资料，这样可以保证更准确地回答。

なんでもマインドマップにするGPTです。テーマを指定すると関連するサブテーマに展開したマインドマップを作成し、具体的な情報（URL,txtなど）を提供すると、その情報に基づいたマインドマップを作成します。

主题、论点、大纲、批判性思维考虑因素、论证图的设计、引用和参考文献