Best AI tools for< Research Papers >

Papers With Code is an AI tool that provides access to the latest research papers in the field of Machine Learning, along with corresponding code implementations. It offers a platform for researchers and enthusiasts to stay updated on state-of-the-art datasets, methods, and trends in the ML domain. Users can explore a wide range of topics such as language modeling, image generation, virtual try-on, and more through the collection of papers and code available on the website.

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.

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.

Explainpaper is an AI-powered tool designed to simplify and explain complex research papers. Users can upload a paper, highlight confusing text, and receive explanations to make the content easier to understand. The tool leverages AI and machine learning models to break down dense sections and clarify intricate concepts, ultimately making research papers more accessible to a wider audience. It is a valuable resource for researchers, students, and anyone looking to delve into complex topics with confidence.

Google Research is a leading research organization focusing on advancing science and artificial intelligence. They conduct research in various domains such as AI/ML foundations, responsible human-centric technology, science & societal impact, computing paradigms, and algorithms & optimization. Google Research aims to create an environment for diverse research across different time scales and levels of risk, driving advancements in computer science through fundamental and applied research. They publish hundreds of research papers annually, collaborate with the academic community, and work on projects that impact technology used by billions of people worldwide.

Google Research is a team of scientists and engineers working on a wide range of topics in computer science, including artificial intelligence, machine learning, and quantum computing. Our mission is to advance the state of the art in these fields and to develop new technologies that can benefit society. We publish hundreds of research papers each year and collaborate with researchers from around the world. Our work has led to the development of many new products and services, including Google Search, Google Translate, and Google Maps.

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.

Papertalk.io is an AI-powered platform that revolutionizes research by providing users with access to over 215 million papers, AI-generated explanations, and actionable insights. The platform offers precision search tools, AI-powered understanding of research papers, and personalized guidance on applying insights practically. Papertalk.io aims to make research more accessible and approachable for users from diverse backgrounds, transforming complex data into easy-to-digest formats to foster innovation and expertise.

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.

PaperGuide.AI is an AI-powered research platform that helps users discover, read, write, and manage research with ease. It offers features such as AI search to discover new papers, summaries to understand complex research, reference management, note-taking, and AI writing assistance. Trusted by over 500,000 users, PaperGuide.AI streamlines academic and research workflows by providing tools to synthesize research faster, manage references effectively, and write essays and research papers efficiently.

RapidAI Research Institute is an academic institution under the RapidAI open-source organization, a non-enterprise academic institution. It serves as a platform for academic research and collaboration, providing opportunities for aspiring researchers to publish papers and engage in scholarly activities. The institute offers mentorship programs and benefits for members, including access to resources such as internet connectivity, GPU configurations, and storage space. The management team consists of esteemed professionals in the field, ensuring a conducive environment for academic growth and development.

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.

Summarize Paper .com is an open-source AI tool that provides concise, understandable, and insightful summaries of the latest research articles on arXiv. The tool uses AI to generate key points and layman's summaries of research papers, making it easy for users to stay up-to-date with the latest developments in their field. In addition to its summary service, Summarize Paper .com also offers an AI assistant that can answer questions about arXiv papers. The tool is designed to make it easy for researchers, students, journalists, and anyone else who wants to stay informed about the latest research to access and understand the latest findings.

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.

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.

Editage is a professional editing, translation, and publication support services company that enables academicians, researchers, scientists, and authors worldwide to publish their work in the best light. Over the past two decades, Editage has helped 500,000+ researchers across 192+ countries to pursue successful publications. The goal is to help researchers improve the quality of their research and increase their chances of publication in international indexed journals.

Google Colab is a free Jupyter notebook environment that runs in the cloud. It allows you to write and execute Python code without having to install any software or set up a local environment. Colab notebooks are shareable, so you can easily collaborate with others on projects.

Avidnote is an AI tool designed for research writing, reading, and analysis. It enables users to write or read research papers faster, analyze research data with AI templates, summarize text, find research gaps, transcribe interviews, and more. Avidnote offers AI functionalities tailored for researchers, recommended by universities, and supported by researchers worldwide. The platform provides free and paid plans with varying features and benefits to cater to different user needs.

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.

Dr.Oracle is a personal AI research assistant that helps you find and understand the latest research in your field. With Dr.Oracle, you can search for research papers, track your favorite authors, and get personalized recommendations for new research. Dr.Oracle is the perfect tool for students, researchers, and anyone who wants to stay up-to-date on the latest research in their field.

The NewEraAI-Papers repository provides links to collections of influential and interesting research papers from top AI conferences, along with open-source code to promote reproducibility and provide detailed implementation insights beyond the scope of the article. Users can stay up to date with the latest advances in AI research by exploring this repository. Contributions to improve the completeness of the list are welcomed, and users can create pull requests, open issues, or contact the repository owner via email to enhance the repository further.

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.

This repository is a collection of research lectures and experience sharing posts from frontline researchers in the field of AI. It aims to help individuals upgrade their research skills and knowledge through insightful talks and experiences shared by experts. The content covers various topics such as evaluating research papers, choosing research directions, research methodologies, and tips for writing high-quality scientific papers. The repository also includes discussions on academic career paths, research ethics, and the emotional aspects of research work. Overall, it serves as a valuable resource for individuals interested in advancing their research capabilities in the field of AI.

This repository maintains a list of research papers on LLM-based Multi-Agents, categorized into five main streams: Multi-Agents Framework, Multi-Agents Orchestration and Efficiency, Multi-Agents for Problem Solving, Multi-Agents for World Simulation, and Multi-Agents Datasets and Benchmarks. The repository also includes a survey paper on LLM-based Multi-Agents and a table summarizing the key findings of the survey.

This repository provides a comprehensive survey of research papers on large language model (LLM)-based game agents. LLMs are powerful AI models that can understand and generate human language, and they have shown great promise for developing intelligent game agents. This survey covers a wide range of topics, including adventure games, crafting and exploration games, simulation games, competition games, cooperation games, communication games, and action games. For each topic, the survey provides an overview of the state-of-the-art research, as well as a discussion of the challenges and opportunities for future work.

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 is a curated list of papers focused on the detection of Large Language Models (LLMs)-generated content. It includes the latest research papers covering detection methods, datasets, attacks, and more. The repository is regularly updated to include the most recent papers in the field.

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.

The AI Scientist is a comprehensive system for fully automatic scientific discovery, enabling Foundation Models to perform research independently. It aims to tackle the grand challenge of developing agents capable of conducting scientific research and discovering new knowledge. The tool generates papers on various topics using Large Language Models (LLMs) and provides a platform for exploring new research ideas. Users can create their own templates for specific areas of study and run experiments to generate papers. However, caution is advised as the codebase executes LLM-written code, which may pose risks such as the use of potentially dangerous packages and web access.

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

This repository is a curated list of papers related to 3D tasks empowered by Large Language Models (LLMs). It covers tasks such as 3D understanding, reasoning, generation, and embodied agents. The repository also includes other Foundation Models like CLIP and SAM to provide a comprehensive view of the area. It is actively maintained and updated to showcase the latest advances in the field. Users can find a variety of research papers and projects related to 3D tasks and LLMs in this repository.

This repository contains a collection of research papers related to watermarking techniques for text and images, specifically focusing on large language models (LLMs). The papers cover various aspects of watermarking LLM-generated content, including robustness, statistical understanding, topic-based watermarks, quality-detection trade-offs, dual watermarks, watermark collision, and more. Researchers have explored different methods and frameworks for watermarking LLMs to protect intellectual property, detect machine-generated text, improve generation quality, and evaluate watermarking techniques. The repository serves as a valuable resource for those interested in the field of watermarking for LLMs.

This repository is a curated list of research papers that explore the integration of Large Language Model (LLM) technology with tabular data. It aims to provide a comprehensive resource for researchers and practitioners interested in this emerging field. The repository includes papers on a wide range of topics, including table-to-text generation, table question answering, and tabular data classification. It also includes a section on related datasets and resources.

Data-to-paper is an AI-driven framework designed to guide users through the process of conducting end-to-end scientific research, starting from raw data to the creation of comprehensive and human-verifiable research papers. The framework leverages a combination of LLM and rule-based agents to assist in tasks such as hypothesis generation, literature search, data analysis, result interpretation, and paper writing. It aims to accelerate research while maintaining key scientific values like transparency, traceability, and verifiability. The framework is field-agnostic, supports both open-goal and fixed-goal research, creates data-chained manuscripts, involves human-in-the-loop interaction, and allows for transparent replay of the research process.

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.

AudioLLMs is a curated collection of research papers focusing on developing, implementing, and evaluating language models for audio data. The repository aims to provide researchers and practitioners with a comprehensive resource to explore the latest advancements in AudioLLMs. It includes models for speech interaction, speech recognition, speech translation, audio generation, and more. Additionally, it covers methodologies like multitask audioLLMs and segment-level Q-Former, as well as evaluation benchmarks like AudioBench and AIR-Bench. Adversarial attacks such as VoiceJailbreak are also discussed.

Awesome LLM Strawberry is a collection of research papers and blogs related to OpenAI Strawberry(o1) and Reasoning. The repository is continuously updated to track the frontier of LLM Reasoning.

Awesome-llm-role-playing-with-persona is a curated list of resources for large language models for role-playing with assigned personas. It includes papers and resources related to persona-based dialogue systems, personalized response generation, psychology of LLMs, biases in LLMs, and more. The repository aims to provide a comprehensive collection of research papers and tools for exploring role-playing abilities of large language models in various contexts.

Awesome Mamba is a curated collection of groundbreaking research papers and articles on Mamba Architecture, a pioneering framework in deep learning known for its selective state spaces and efficiency in processing complex data structures. The repository offers a comprehensive exploration of Mamba architecture through categorized research papers covering various domains like visual recognition, speech processing, remote sensing, video processing, activity recognition, image enhancement, medical imaging, reinforcement learning, natural language processing, 3D recognition, multi-modal understanding, time series analysis, graph neural networks, point cloud analysis, and tabular data handling.

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.

Explains Arxiv papers with examples, analogies, and direct PDF links.

Find and summarize recent papers in biology, chemistry, and biomedical sciences.

Drafts detailed research papers with web-sourced citations, following user-specific instructions.

Expert assistant for writing academic research papers.

Expert in crafting high-standard research papers.

Editing and polishing your research papers professionally in an easy way!

Stay up to date with Arxiv Research Papers!

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

A GPT with Knowledge of the most recent papers in Machine Learning`

Your AI research aide for the latest in ML.

Summarizes papers or titles provided by the user.

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.

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

A Specialized Biochemistry and Pharmaceutical Research Assistant

論文のPDFをアップロードすると、内容を日本語で分かりやすく説明します（OpenAI側の問題により、論文URLでの解説機能は一時停止しています）。This is the Japanese version of Paper Interpreter. The international version is available at https://chat.openai.com/g/g-R9Dry2N5h-paper-interpreter

是一个可以帮助你撰写核心期刊研究性论文的功能。可以根据你的研究问题、研究目的、研究方法、研究结果和研究结论等信息，为你生成一份符合格式要求和内容要求的研究性论文草稿，包括标题、摘要、关键词、引言、文献综述、研究设计、数据分析、讨论和参考文献等。还可以提供一些参考文献和范文，帮助你完善和优化你的研究性论文。

Academic writer for SCI papers on lung nodule procedures.

Teaches and analyzes research methods with in-depth, academic insights.

An assistant for all you research needs

Research Proposal Assistant Pro is designed to provide tailored assistance in research writing.