Best AI tools for< Extract Research Papers >

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.

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.

ScholarAI is an AI-powered scientific research tool that offers a wide range of features to help users navigate and extract insights from scientific literature. With access to over 200 million peer-reviewed articles, ScholarAI allows users to conduct abstract searches, literature mapping, PDF reading, literature reviews, gap analysis, direct Q&A, table and figure extraction, citation management, and project management. The tool is designed to accelerate the research process and provide tailored scientific insights to users.

SciSpace is an AI-powered tool that helps researchers understand research papers better. It can explain and elaborate most academic texts in simple words. It is a great tool for students, researchers, and anyone who wants to learn more about a particular topic. SciSpace has a user-friendly interface and is easy to use. Simply upload a research paper or enter a URL, and SciSpace will do the rest. It will highlight key concepts, provide definitions, and generate a summary of the paper. SciSpace can also be used to generate citations and find related papers.

ArxivPaperAI is an AI-powered research paper summarizer that helps you quickly and easily understand the key points of academic papers. With ArxivPaperAI, you can:

The FileAI website offers an AI-powered file reading assistant that specializes in data extraction from structured documents like financial statements, legal documents, and research papers. It automates tasks related to legal and compliance review, finance and accounting report preparation, and research and academia support. The tool aims to streamline document processing, enhance learning processes, and improve research efficiency. With features like summarizing complex texts, extracting key information, and detecting plagiarism, FileAI caters to users in various industries and educational fields. The platform prioritizes data security and user privacy, ensuring that data is used solely for its intended purpose and deleted after 7 days of non-use.

Humata is a PDF AI that can summarize findings, compare documents, and search for answers in long technical papers. It is designed to help users save time and effort by automating the process of reading and understanding complex documents. Humata is easy to use and can be embedded in any webpage with a single click. It is also secure and reliable, with enterprise-grade data rooms and encryption to protect user data.

UpSum is a text summarization tool that uses advanced AI technology to condense lengthy texts into concise summaries. It is designed to save users time and effort by extracting the key points and insights from documents, research papers, news articles, and other written content. UpSum's AI algorithm analyzes the text, identifies the most important sentences and phrases, and assembles them into a coherent summary that accurately represents the main ideas and key takeaways of the original text. The tool is easy to use, simply upload or paste your text, select the desired summary length, and click the summarize button. UpSum is available as a free web-based tool, as well as a premium subscription with additional features and capabilities.

Brevity is an AI tool designed to transform long-form content into clear and concise summaries. It helps users save time by providing quick and efficient summaries of lengthy texts. With Brevity, users can easily extract key information without having to read through entire documents. The tool is user-friendly and suitable for various industries and purposes, making it a valuable asset for anyone looking to streamline their reading and research process.

Skim.ai is an AI-powered tool designed to assist users in summarizing and extracting key information from text. By leveraging advanced natural language processing algorithms, Skim.ai can quickly analyze and condense lengthy documents, articles, or web pages into concise summaries. Users can easily access the summarized content, saving time and effort in information consumption. Skim.ai aims to enhance productivity and efficiency by providing a streamlined way to digest and comprehend textual data.

Epsilon is an AI search engine designed for scientific research solutions. It helps researchers find evidence, citations, and relevant information from over 200 million academic papers. Epsilon can summarize passages, group search results, extract key information from multiple papers, and provide comprehensive summaries. Trusted by over 30,000 researchers worldwide, Epsilon is a reliable tool for conducting literature reviews, drafting proposals, and executing research projects.

Otio is an AI research and writing partner powered by o3-mini, Claude 3.7, and Gemini 2.0. It offers a fast and efficient way to do research by summarizing and chatting with documents, writing and editing in an AI text editor, and automating workflows. Otio is trusted by over 200,000 researchers and students, providing detailed, structured AI summaries, automatic summaries for various types of content, chat capabilities, and workflow automation. Users can extract insights from research quickly, automate repetitive tasks, and edit their writing with AI assistance.

Buzzabout is an AI audience research tool that provides insights from thousands of discussions on Reddit in seconds. It helps users save time by extracting key opinions and meanings quickly, allowing them to understand their audience without leaving Slack. The tool enables users to chat with their audience, interview hundreds of customers simultaneously, and receive instant replies by AI persona. Buzzabout offers various pricing plans with features like sentiment analysis, trend analysis, and shareable reports to support decision-making and improve products and marketing strategies.

PromptLoop is an AI-powered web scraping and data extraction platform that allows users to run AI automation tasks on lists of data with a simple file upload. It enables users to crawl company websites, categorize entities, and conduct research tasks at a fraction of the cost of other alternatives. By leveraging unique company data from spreadsheets, PromptLoop enables the creation of custom AI models tailored to specific needs, facilitating the extraction of valuable insights from complex information.

PromptLoop is an AI-powered tool that integrates with Excel and Google Sheets to enhance market research and data analysis. It offers custom AI models tailored to specific needs, enabling users to extract insights from complex information. With PromptLoop, users can leverage advanced AI capabilities for tasks such as web research, content analysis, and data labeling, streamlining workflows and improving efficiency.

Genei is an AI-powered summarization and research tool that helps users with qualitative research, content production, academic writing, and professional writing. It enables users to research faster by automatically summarizing background reading and producing blogs, articles, and reports efficiently. Genei offers features such as summarization, keyword extraction, document management, annotation capabilities, and citation management. Trusted by thought leaders and experts, Genei enhances productivity, saves time, and improves the quality and efficiency of research and writing tasks.

Otio is an AI-native workspace designed for research and writing, powered by advanced models like GPT-4, Claude 3, and Mistral. It offers features such as summarizing and chatting with documents, writing, editing, and paraphrasing with AI assistance. Otio is trusted by researchers, students, and analysts from top institutions, providing a simple and efficient way to collect, read, and write in a single workspace. The tool aims to streamline the research process by summarizing various types of content, generating first drafts, and helping users extract key insights quickly.

Bard PDF is an AI-powered tool that allows users to interact with PDF documents through natural language conversation. It can summarize documents, answer questions, and extract key information. Bard PDF is designed to help researchers, students, and professionals save time and improve their productivity.

PDFMerse is an AI-powered data extraction tool that revolutionizes how users handle document data. It allows users to effortlessly extract information from PDFs with precision, saving time and enhancing workflow. With cutting-edge AI technology, PDFMerse automates data extraction, ensures data accuracy, and offers versatile output formats like CSV, JSON, and Excel. The tool is designed to dramatically reduce processing time and operational costs, enabling users to focus on higher-value tasks.

AlphaResearch is an AI-powered search engine and research platform for investors. It provides access to millions of global filings, transcripts, press releases, and reports, and uses machine learning and NLP techniques to extract insights from text data. AlphaResearch helps investors save time on research, understand market sentiment, and make better investment decisions.

OneFileLLM is a command-line tool that streamlines the creation of information-dense prompts for large language models (LLMs). It aggregates and preprocesses data from various sources, compiling them into a single text file for quick use. The tool supports automatic source type detection, handling of multiple file formats, web crawling functionality, integration with Sci-Hub for research paper downloads, text preprocessing, token count reporting, and XML encapsulation of output for improved LLM performance. Users can easily access private GitHub repositories by generating a personal access token. The tool's output is encapsulated in XML tags to enhance LLM understanding and processing.

PapersGPT For Zotero is an AI plugin that enhances papers reading and research efficiency by integrating cutting-edge LLMs and offering seamless Zotero integration. Users can ask questions, extract insights, and converse with PDFs directly, making it a powerful research assistant for scholars, researchers, and anyone dealing with large amounts of text in PDF format. The plugin ensures privacy and data safety by using locally stored models and modules, with the ability to switch between different models easily. It provides a user-friendly interface for managing and chatting documents within Zotero, making research tasks more streamlined and productive.

The 'ai4math-papers' repository contains a collection of research papers related to AI applications in mathematics, including automated theorem proving, synthetic theorem generation, autoformalization, proof refactoring, premise selection, benchmarks, human-in-the-loop interactions, and constructing examples/counterexamples. The papers cover various topics such as neural theorem proving, reinforcement learning for theorem proving, generative language modeling, formal mathematics statement curriculum learning, and more. The repository serves as a valuable resource for researchers and practitioners interested in the intersection of AI and mathematics.

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.

CodeLLM Paper repository provides a curated list of research papers focused on Large Language Models (LLMs) for code. It aims to facilitate researchers and practitioners in exploring the rapidly growing body of literature on this topic. The papers are systematically collected from various top-tier venues, categorized, and labeled for easier navigation. The selection strategy involves abstract extraction, keyword matching, relevance check using LLMs, and manual labeling. The papers are categorized based on Application, Principle, and Research Paradigm dimensions. Contributions to expand the repository are welcome through PR submission, issue submission, or request for batch updates. The repository is intended solely for research purposes, with raw data sourced from publicly available information on ACM, IEEE, and corresponding conference websites.

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.

DeepSeek is a new experimental architecture for a large language model (LLM) powered internet-scale retrieval engine. Unlike current research agents designed as answer engines, DeepSeek aims to process a vast amount of sources to collect a comprehensive list of entities and enrich them with additional relevant data. The end result is a table with retrieved entities and enriched columns, providing a comprehensive overview of the topic. DeepSeek utilizes both standard keyword search and neural search to find relevant content, and employs an LLM to extract specific entities and their associated contents. It also includes a smaller answer agent to enrich the retrieved data, ensuring thoroughness. DeepSeek has the potential to revolutionize research and information gathering by providing a comprehensive and structured way to access information from the vastness of the internet.

1filellm is a command-line data aggregation tool designed for LLM ingestion. It aggregates and preprocesses data from various sources into a single text file, facilitating the creation of information-dense prompts for large language models. The tool supports automatic source type detection, handling of multiple file formats, web crawling functionality, integration with Sci-Hub for research paper downloads, text preprocessing, and token count reporting. Users can input local files, directories, GitHub repositories, pull requests, issues, ArXiv papers, YouTube transcripts, web pages, Sci-Hub papers via DOI or PMID. The tool provides uncompressed and compressed text outputs, with the uncompressed text automatically copied to the clipboard for easy pasting into LLMs.

Marly is a tool that allows users to search for and extract context-specific data from various types of documents such as PDFs, Word files, Powerpoints, and websites. It provides the ability to extract data in structured formats like JSON or Markdown, making it easy to integrate into workflows. Marly supports multi-schema and multi-document extraction, offers built-in caching for rapid repeat extractions, and ensures no vendor lock-in by allowing flexibility in choosing model providers.

RD-Agent is a tool designed to automate critical aspects of industrial R&D processes, focusing on data-driven scenarios to streamline model and data development. It aims to propose new ideas ('R') and implement them ('D') automatically, leading to solutions of significant industrial value. The tool supports scenarios like Automated Quantitative Trading, Data Mining Agent, Research Copilot, and more, with a framework to push the boundaries of research in data science. Users can create a Conda environment, install the RDAgent package from PyPI, configure GPT model, and run various applications for tasks like quantitative trading, model evolution, medical prediction, and more. The tool is intended to enhance R&D processes and boost productivity in industrial settings.

OneKE is a flexible dockerized system for schema-guided knowledge extraction, capable of extracting information from the web and raw PDF books across multiple domains like science and news. It employs a collaborative multi-agent approach and includes a user-customizable knowledge base to enable tailored extraction. OneKE offers various IE tasks support, data sources support, LLMs support, extraction method support, and knowledge base configuration. Users can start with examples using YAML, Python, or Web UI, and perform tasks like Named Entity Recognition, Relation Extraction, Event Extraction, Triple Extraction, and Open Domain IE. The tool supports different source formats like Plain Text, HTML, PDF, Word, TXT, and JSON files. Users can choose from various extraction models like OpenAI, DeepSeek, LLaMA, Qwen, ChatGLM, MiniCPM, and OneKE for information extraction tasks. Extraction methods include Schema Agent, Extraction Agent, and Reflection Agent. The tool also provides support for schema repository and case repository management, along with solutions for network issues. Contributors to the project include Ningyu Zhang, Haofen Wang, Yujie Luo, Xiangyuan Ru, Kangwei Liu, Lin Yuan, Mengshu Sun, Lei Liang, Zhiqiang Zhang, Jun Zhou, Lanning Wei, Da Zheng, and Huajun Chen.

This project focuses on implementing Sparse Autoencoders (SAEs) for mechanistic interpretability in Large Language Models (LLMs) like Llama 3.2-3B. The SAEs aim to untangle superimposed representations in LLMs into separate, interpretable features for each neuron activation. The project provides an end-to-end pipeline for capturing training data, training the SAEs, analyzing learned features, and verifying results experimentally. It includes comprehensive logging, visualization, and checkpointing of SAE training, interpretability analysis tools, and a pure PyTorch implementation of Llama 3.1/3.2 chat and text completion. The project is designed for scalability, efficiency, and maintainability.

Nightshade Antidote is an image forensics tool used to analyze digital images for signs of manipulation or forgery. It implements several common techniques used in image forensics including metadata analysis, copy-move forgery detection, frequency domain analysis, and JPEG compression artifacts analysis. The tool takes an input image, performs analysis using the above techniques, and outputs a report summarizing the findings.

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

This repository serves as a practical guide for Medical Large Language Models (Medical LLMs) and provides resources, surveys, and tools for building, fine-tuning, and utilizing LLMs in the medical domain. It covers a wide range of topics including pre-training, fine-tuning, downstream biomedical tasks, clinical applications, challenges, future directions, and more. The repository aims to provide insights into the opportunities and challenges of LLMs in medicine and serve as a practical resource for constructing effective medical LLMs.

A comprehensive repository of resources for Chinese large language models (LLMs), including data processing tools, fine-tuning frameworks, inference libraries, evaluation platforms, RAG engines, agent frameworks, books, courses, tutorials, and tips. The repository covers a wide range of tools and resources for working with LLMs, from data labeling and processing to model fine-tuning, inference, evaluation, and application development. It also includes resources for learning about LLMs through books, courses, and tutorials, as well as insights and strategies from building with LLMs.

マルチモーダルデータからの情報抽出と解析を専門とする

Generate a structured abstract for academic papers, primarily in the field of biology, adhering to a specified word count range. Simply upload your manuscript file (without the abstract) and specify the word count (for example, '200-250') to GPT.

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

专业总结学术论文核心贡献和方法

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.

Analyze watch images, extract text, and craft sales descriptions. Add 1 or more images for a single watch to get started.

Assists with text extraction from PDFs

Expert in extracting and transcribing text from images.

从网址提取并选择模型计算大小

Professional news analysis expert, verifying article authenticity with in-depth research and unbiased evaluation.

Put your prompt engineering skills to the ultimate test! Embark on a journey to outwit a mythical guardian of ancient secrets. Try to extract the secret passphrase hidden in the system prompt and enter it in chat when you think you have it and claim your glory. Good luck!

A GPT specializing in historical primary source analysis

Expert in data extraction and context-driven analysis. Can read most filetypes including PDFS, XLSX, Word, TXT, CSV, EML, Etc.

Extracts and structures web content in formal, technical language.

Expert in web scraping with python and Pycharm.

Expertly synthesizes complex info into clear, concise insights.

请输入文章或者上载文件，专门于文档分析的阅读助手，会使用中文回复。

I provide insights and summaries of PDF documents uploaded by users.

Image & document analysis expert

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