Best AI tools for< Analyze Paper >

Elicit is an AI research assistant that helps researchers analyze research papers at superhuman speed. It automates time-consuming research tasks such as summarizing papers, extracting data, and synthesizing findings. Trusted by researchers, Elicit offers a plethora of features to speed up the research process and is particularly beneficial for empirical domains like biomedicine and machine learning.

scienceOS is an AI research tool designed for scientists to accelerate their research process. It offers features such as AI science chat, AI PDF chat, AI reference manager, and more to help researchers access and analyze vast amounts of scientific data efficiently. With a focus on collaboration, simplicity, leanness, and vision, scienceOS aims to empower scientists in tackling global challenges by providing access to a vast database of research papers and citations.

Elicit is a research tool that uses artificial intelligence to help researchers analyze research papers more efficiently. It can summarize papers, extract data, and synthesize findings, saving researchers time and effort. Elicit is used by over 800,000 researchers worldwide and has been featured in publications such as Nature and Science. It is a powerful tool that can help researchers stay up-to-date on the latest research and make new discoveries.

PdfPal AI is an innovative AI-powered application that allows users to interact with PDF documents through intelligent conversations. Users can upload any PDF document, ask questions, receive instant answers, obtain summaries, and gain valuable insights effortlessly. The application is designed to simplify complex documents, guide users through content, and provide intelligent analysis, making it a valuable tool for individuals across various industries.

AskDocs is an AI-powered document assistant designed to help users read faster and create better work content. It offers cross-document analysis, quick answers linked to documents, one-click summaries of key concepts, and the ability to understand confusing information. With a focus on enhancing productivity, AskDocs is trusted by students, knowledge workers, and small businesses to streamline research, meeting notes, emails, and more. The tool supports various document types and provides instant answers directly linked to sources within the uploaded documents.

Undermind is an AI-powered scientific research assistant that revolutionizes the way researchers access and analyze academic papers. By utilizing intelligent language models, Undermind reads and synthesizes information from hundreds of papers to provide accurate and comprehensive results. Researchers can describe their queries in natural language, and Undermind assists in finding relevant papers, brainstorming questions, and discovering crucial insights. Trusted by researchers across various fields, Undermind offers a unique approach to literature search, surpassing traditional search engines in accuracy and efficiency.

Paper Interpreter is an AI application developed by Daichi Konno, a medical doctor and neuroscientist at the University of Tokyo. The application allows users to input a PDF or URL of a research paper and receive a simplified explanation generated by an AI assistant. It gained significant popularity shortly after its release, ranking 6th globally and 1st in Japan in terms of usage. The tool aims to make academic research more accessible and understandable to a wider audience.

AI Paper Writer is an online tool that can generate essays, articles, and other types of text within seconds. It uses artificial intelligence to analyze your topic and create unique, high-quality content that is tailored to your specific needs. With AI Paper Writer, you can save time and energy while getting the help you need to complete your writing assignments.

Peslac AI is an intelligent document processing and data extraction tool that streamlines document-heavy processes with advanced AI technology. It offers solutions for automating document processing, extracting data, verifying documents, processing forms, and workflow automation. Peslac serves industries such as insurance, finance, healthcare, legal, and others by providing tailored solutions to improve efficiency and accuracy in operations.

Jotlify is an AI-powered platform that simplifies complex research papers, making them accessible and easy to understand for students, researchers, professionals, and curious minds. It transforms dense academic content into engaging stories and insights, bridging the gap between complex research and easy understanding. With Jotlify, users can uncover stories and insights that can transform their understanding and impact various aspects of their lives.

PYQ is an AI-powered platform that helps businesses automate document-related tasks, such as data extraction, form filling, and system integration. It uses natural language processing (NLP) and machine learning (ML) to understand the content of documents and perform tasks accordingly. PYQ's platform is designed to be easy to use, with pre-built automations for common use cases. It also offers custom automation development services for more complex needs.

Floatz is an AI tool designed for scientific research, aimed at inspiring individuals to create extraordinary things. The platform leverages artificial intelligence to assist researchers in their work, providing innovative solutions and insights to drive scientific discoveries. With a focus on creativity and imagination, Floatz empowers users to explore new possibilities and push the boundaries of knowledge in various fields of study.

OpExams is an AI-powered platform designed to assist educators in creating, administering, grading, and analyzing exams. It offers features such as online exams, quizzes, paper exams, code assignments, interactive lessons, AI questions generator, and AI quiz generator. OpExams aims to streamline the exam preparation process for teachers by providing tools from the future, making it effortless to manage various types of assessments. With a global community of educators using OpExams, the platform is revolutionizing the traditional exam procedures and enhancing the teaching and learning experience worldwide.

Essay Grader AI is an AI-powered essay grading tool designed to help teachers streamline their grading process. It allows teachers to upload student submissions, apply customized rubrics, and receive instant, accurate grades and detailed feedback. The tool supports multiple languages and subjects, ensuring fair and consistent grading while saving teachers time and providing actionable insights to improve student writing proficiency.

Wizdom.ai is an AI-powered research intelligence platform that provides comprehensive insights into the global research ecosystem. It continuously monitors billions of data points to generate analytics about scientific developments, helping users make informed decisions and progress research further and faster. Wizdom.ai offers a range of features, including:

SciSummary is an AI tool designed to summarize scientific articles and research papers quickly and efficiently. It utilizes advanced AI technology, specifically GPT-3.5 and GPT-4 models, to provide accurate and concise summaries for busy scientists, students, and enthusiasts. The platform allows users to submit documents via email, upload articles to the dashboard, or attach PDFs for summarization. With features like unlimited summaries, figure and table analysis, and chat messages, SciSummary is a valuable resource for researchers looking to stay updated with the latest trends in research.

iLovePhD is a comprehensive research platform that serves as a one-stop solution for all research needs. It offers a wide range of services including access to journals, postdoc opportunities, scholarships, IoT security tools, job listings, datasets, and UGC-CARE journals. The platform also features ChatGPT for plagiarism detection and artificial intelligence applications. iLovePhD aims to assist researchers and academicians in publishing impactful work and staying updated with the latest trends in the academic world.

Kudra is an AI-powered data extraction tool that offers dedicated solutions for finance, human resources, logistics, legal, and more. It effortlessly extracts critical data fields, tables, relationships, and summaries from various documents, transforming unstructured data into actionable insights. Kudra provides customizable AI models, seamless integrations, and secure document processing while supporting over 20 languages. With features like custom workflows, model training, API integration, and workflow builder, Kudra aims to streamline document processing for businesses of all sizes.

Chargezoom is an AI-powered accounts receivable (AR) solution that helps businesses get paid faster. It automates many of the tasks associated with AR, such as invoicing, payment reminders, and reconciliation. Chargezoom also provides businesses with insights into their AR performance, so they can make better decisions about how to manage their cash flow. Chargezoom is a cloud-based solution that is easy to use and integrates with a variety of accounting software programs.

Eklavvya.AI is an AI-powered platform offering practice tests, practice interviews, and exam question papers with answers. It provides a comprehensive solution for exam preparation by leveraging cutting-edge technology to personalize education and revolutionize the studying process. The platform offers a wide range of practice exams, school exams, and CET exams for various subjects and courses. Additionally, it features multilingual tests, detailed performance analytics, and walkthroughs for better learning outcomes.

The ArXiv MCP Server acts as a bridge between AI assistants and arXiv's research repository, enabling AI models to search for and access papers programmatically through the Message Control Protocol (MCP). It offers features like paper search, access, listing, local storage, and research prompts. Users can install it via Smithery or manually for Claude Desktop. The server provides tools for paper search, download, listing, and reading, along with specialized prompts for paper analysis. Configuration can be done through environment variables, and testing is supported with a test suite. The tool is released under the MIT License and is developed by the Pearl Labs Team.

Since the emergence of chatGPT in 2022, the acceleration of Large Language Model has become increasingly important. Here is a list of papers on LLMs inference and serving.

Awesome-Papers-Autonomous-Agent is a curated collection of recent papers focusing on autonomous agents, specifically interested in RL-based agents and LLM-based agents. The repository aims to provide a comprehensive resource for researchers and practitioners interested in intelligent agents that can achieve goals, acquire knowledge, and continually improve. The collection includes papers on various topics such as instruction following, building agents based on world models, using language as knowledge, leveraging LLMs as a tool, generalization across tasks, continual learning, combining RL and LLM, transformer-based policies, trajectory to language, trajectory prediction, multimodal agents, training LLMs for generalization and adaptation, task-specific designing, multi-agent systems, experimental analysis, benchmarking, applications, algorithm design, and combining with RL.

CopilotKit is an open-source framework for building, deploying, and operating fully custom AI Copilots, including in-app AI chatbots, AI agents, and AI Textareas. It provides a set of components and entry points that allow developers to easily integrate AI capabilities into their applications. CopilotKit is designed to be flexible and extensible, so developers can tailor it to their specific needs. It supports a variety of use cases, including providing app-aware AI chatbots that can interact with the application state and take action, drop-in replacements for textareas with AI-assisted text generation, and in-app agents that can access real-time application context and take action within the application.

This repository, Awesome-LLM-RAG, aims to record advanced papers on Retrieval Augmented Generation (RAG) in Large Language Models (LLMs). It serves as a resource hub for researchers interested in promoting their work related to LLM RAG by updating paper information through pull requests. The repository covers various topics such as workshops, tutorials, papers, surveys, benchmarks, retrieval-enhanced LLMs, RAG instruction tuning, RAG in-context learning, RAG embeddings, RAG simulators, RAG search, RAG long-text and memory, RAG evaluation, RAG optimization, and RAG applications.

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.

The 'LLMs-in-science' repository is a collaborative environment for organizing papers related to large language models (LLMs) and autonomous agents in the field of chemistry. The goal is to discuss trend topics, challenges, and the potential for supporting scientific discovery in the context of artificial intelligence. The repository aims to maintain a systematic structure of the field and welcomes contributions from the community to keep the content up-to-date and relevant.

This repository is a collection of papers and resources related to Lifelong Learning of Large Language Model (LLM) based Agents. It focuses on continual learning and incremental learning of LLM agents, identifying key modules such as Perception, Memory, and Action. The repository serves as a roadmap for understanding lifelong learning in LLM agents and provides a comprehensive overview of related research and surveys.

LLM-Agent-Survey is a comprehensive repository that provides a curated list of papers related to Large Language Model (LLM) agents. The repository categorizes papers based on LLM-Profiled Roles and includes high-quality publications from prestigious conferences and journals. It aims to offer a systematic understanding of LLM-based agents, covering topics such as tool use, planning, and feedback learning. The repository also includes unpublished papers with insightful analysis and novelty, marked for future updates. Users can explore a wide range of surveys, tool use cases, planning workflows, and benchmarks related to LLM agents.

A Collection of Papers and Codes for CVPR 2024 AIGC. This repository compiles and organizes research papers and code related to CVPR 2024 and ECCV 2024 AIGC (Artificial Intelligence and Graphics Computing). It serves as a valuable resource for individuals interested in the latest advancements in the field of computer vision and artificial intelligence. Users can find a curated list of papers and accompanying code repositories for further exploration and research. The repository encourages collaboration and contributions from the community through stars, forks, and pull requests.

The Eureka Framework is an open-source toolkit that leverages advanced Artificial Intelligence and Decentralized Science principles to revolutionize scientific discovery. It enables researchers, developers, and decentralized organizations to explore scientific papers, conduct AI-driven experiments, monetize research contributions, provide token-gated access to AI agents, and customize AI agents for specific research domains. The framework also offers features like a RESTful API, robust scheduler for task automation, and webhooks for real-time notifications, empowering users to automate research tasks, enhance productivity, and foster a committed research community.

This repository contains example code to demonstrate how to connect MATLAB to the OpenAI™ Chat Completions API (which powers ChatGPT™) as well as OpenAI Images API (which powers DALL·E™). This allows you to leverage the natural language processing capabilities of large language models directly within your MATLAB environment.

This repository is an updating survey for Continual Learning of Large Language Models (CL-LLMs), providing a comprehensive overview of various aspects related to the continual learning of large language models. It covers topics such as continual pre-training, domain-adaptive pre-training, continual fine-tuning, model refinement, model alignment, multimodal LLMs, and miscellaneous aspects. The survey includes a collection of relevant papers, each focusing on different areas within the field of continual learning of large language models.

Deep Dive into AI with MLX and PyTorch is an educational initiative focusing on AI, machine learning, and deep learning using Apple's MLX and Meta's PyTorch frameworks. The repository contains comprehensive guides, in-depth analyses, and resources for learning and exploring AI concepts. It aims to cater to audiences ranging from beginners to experienced individuals, providing detailed explanations, examples, and translations between PyTorch and MLX. The project emphasizes open-source contributions, knowledge sharing, and continuous learning in the field of AI.

AI for Science paper collection is an initiative by AI for Science Community to collect and categorize papers in AI for Science areas by subjects, years, venues, and keywords. The repository contains `.csv` files with paper lists labeled by keys such as `Title`, `Conference`, `Type`, `Application`, `MLTech`, `OpenReviewLink`. It covers top conferences like ICML, NeurIPS, and ICLR. Volunteers can contribute by updating existing `.csv` files or adding new ones for uncovered conferences/years. The initiative aims to track the increasing trend of AI for Science papers and analyze trends in different applications.

Paperless-AI is an automated document analyzer tool designed for Paperless-ngx users. It utilizes the OpenAI API and Ollama (Mistral, llama, phi 3, gemma 2) to automatically scan, analyze, and tag documents. The tool offers features such as automatic document scanning, AI-powered document analysis, automatic title and tag assignment, manual mode for analyzing documents, easy setup through a web interface, document processing dashboard, error handling, and Docker support. Users can configure the tool through a web interface and access a debug interface for monitoring and troubleshooting. Paperless-AI aims to streamline document organization and analysis processes for users with access to Paperless-ngx and AI capabilities.

The Google Cloud Document AI Samples repository contains code samples and Community Samples demonstrating how to analyze, classify, and search documents using Google Cloud Document AI. It includes various projects showcasing different functionalities such as integrating with Google Drive, processing documents using Python, content moderation with Dialogflow CX, fraud detection, language extraction, paper summarization, tax processing pipeline, and more. The repository also provides access to test document files stored in a publicly-accessible Google Cloud Storage Bucket. Additionally, there are codelabs available for optical character recognition (OCR), form parsing, specialized processors, and managing Document AI processors. Community samples, like the PDF Annotator Sample, are also included. Contributions are welcome, and users can seek help or report issues through the repository's issues page. Please note that this repository is not an officially supported Google product and is intended for demonstrative purposes only.

Yet Another Chatbot is a sophisticated multimodal chat interface powered by advanced AI models and equipped with a variety of tools. This chatbot can search and browse the web in real-time, query Wikipedia for information, perform news and map searches, execute Python code, compose long-form articles mixing text and images, generate, search, and compare images, analyze documents and images, search and download arXiv papers, save conversations as text and audio files, manage checklists, and track personal improvements. It offers tools for web interaction, Wikipedia search, Python scripting, content management, image handling, arXiv integration, conversation generation, file management, personal improvement, and checklist management.

Awesome-Graph-LLM is a curated collection of research papers exploring the intersection of graph-based techniques with Large Language Models (LLMs). The repository aims to bridge the gap between LLMs and graph structures prevalent in real-world applications by providing a comprehensive list of papers covering various aspects of graph reasoning, node classification, graph classification/regression, knowledge graphs, multimodal models, applications, and tools. It serves as a valuable resource for researchers and practitioners interested in leveraging LLMs for graph-related tasks.

Takes in a research paper or article, analyzes its claims, study quality, and results confidence and provides an easy to understand summary.

A specialized tool in UX research, adept at finding, analyzing and communicating UX related research papers and concepts concisely for students and professionals.

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Helps find and analyze ML papers, focusing on SOTA comparisons.

A helpful guide for understanding the paper "Anatomy of an AI-powered malicious social botnet"

Upon uploading a research paper, I provide a concise analysis covering its authors, key findings, methodology, and relevance. I also critique the work, highlight its strengths, and identify any open questions from a professional perspective.

Upon uploading a research paper, I provide a concise section wise analysis covering Abstract, Lit Review, Findings, Methodology, and Conclusion. I also critique the work, highlight its strengths, and answer any open questions from my Knowledge base of Open source materials.

Expertly guides users to identify gaps in research by analyzing and summarizing academic papers.

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Analyzes architectural photos for patterns from "A Pattern Language". (Click the paperclip to upload your photo.)

Summarizes papers or titles provided by the user.

A helpful guide for understanding the paper "Artificial intelligence is ineffective and potentially harmful for fact checking"

I'll analyze academic and scientific articles and create state-of-the-art documents

Summarizes academic papers, especially in medical and scientific research

Know the details about the Amalgamated Intermittent Computing Systems paper

Expert in assisting with IB English Paper 2 exams, focusing on essay guidance and literary analysis.

Especialista em redação de papers acadêmicos em tecnologia da educação.

An Ivy Leage Scholar GPT equipped to understand your research needs, formulate comprehensive literature review strategies, and extract pertinent information from a plethora of academic databases and journals. I'll then compose a peer review-quality paper with citations.

A scholarly geography resource with extensive knowledge from books and papers.

I provide detailed summaries, critiques, and inferences on articles, papers, transcripts, websites, and more. Just give me text, a URL, or file to digest.