Best AI tools for< Scientific Researcher >

Researcher.Life is a comprehensive research support platform that provides AI-powered tools and expert publication services to empower researchers at every stage of their journey. With a suite of advanced AI tools, including Paperpal, R Discovery, and Mind the Graph, Researcher.Life helps researchers write better, discover relevant literature, create stunning scientific illustrations, and find the right journals for their work. Additionally, Researcher.Life offers expert publication services from Editage, ensuring that manuscripts are polished and ready for publication. By combining AI technology with human expertise, Researcher.Life simplifies complex research tasks, saves time, and accelerates the path to success for researchers worldwide.

The website focuses on groundbreaking research in various scientific fields, including quantum communication, semiconductor dynamics, mental health support, dietary interventions, computer vision, autonomous systems safety, movie recommendations, fake cell tower detection, electron-boson interactions, solar observations, network efficiency, galaxy formation, asteroseismology, protein biosynthesis, and high-temperature semiconductor diodes.

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.

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.

Open Knowledge Maps is the world's largest AI-based search engine for scientific knowledge. It aims to revolutionize discovery by increasing the visibility of research findings for science and society. The platform is open and nonprofit, based on the principles of open science, with a mission to create an inclusive, sustainable, and equitable infrastructure for all users. Users can map research topics with AI, find documents, and identify concepts to enhance their literature search experience.

GoatStack is an AI-powered newsletter agent that delivers personalized insights from scientific papers. It reads over 4000 papers daily and handpicks the most relevant ones for you. With GoatStack, you can stay up-to-date on the latest AI breakthroughs and advancements. It offers a range of features to help you customize your newsletter, including the ability to personalize topics, generalize topics, or be specific with content.

Imagetwin is an AI-based software designed to detect integrity issues in figures of scientific articles, specifically in the field of life sciences. The application offers efficient and accurate detection of inappropriate manipulation, duplication, and plagiarism within various types of figures commonly found in scientific publications. Imagetwin is a powerful tool that aids in the peer-review process by automatically identifying integrity issues, ensuring the quality and trustworthiness of scientific research.

arXiv.org is a free distribution service and an open-access archive for nearly 2.4 million scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. Materials on this site are not peer-reviewed by arXiv.

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.

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.

ScienceCast is a platform that enhances scientific papers with interactive media, providing a unique way to explore research findings. Users can create and explore casts in various fields such as Biology, Computer Science, Economics, and more. The platform collaborates with arXiv Labs and is supported by NASA, offering a range of featured casts for in-depth analysis and learning.

PumasAI is an AI tool designed to accelerate access to life-saving treatments for patients by providing data analytics tools and personalized treatments for drug development and healthcare delivery needs. The company has been recognized for its innovative contributions to the pharmaceutical industry, helping in making data-driven decisions more efficiently. PumasAI aims to save time and money for its clients through its fine-tuned offerings and successful regulatory submissions.

The website is a comprehensive platform providing medical news, articles, and resources covering a wide range of health topics such as COVID-19, artificial intelligence in healthcare, diseases, treatments, and medical advancements. It offers insights from experts, interviews, white papers, and newsletters in the fields of medicine and life sciences. Users can access information on various health categories, research findings, safety summaries, and trending stories in the medical and life sciences domains.

wisio is an AI-powered writing assistant that helps scientists write better scientific documents. It provides real-time feedback on grammar, style, and clarity, and it can also help you to generate new ideas and organize your thoughts. wisio is designed to make scientific writing faster, easier, and more effective.

JMIR AI is a new peer-reviewed journal focused on research and applications for the health artificial intelligence (AI) community. It includes contemporary developments as well as historical examples, with an emphasis on sound methodological evaluations of AI techniques and authoritative analyses. It is intended to be the main source of reliable information for health informatics professionals to learn about how AI techniques can be applied and evaluated.

Hepta AI is an AI-powered statistics tool designed for scientific research. It simplifies the process of statistical analysis by allowing users to easily input their data and receive comprehensive results, including tables, graphs, and statistical analysis. With a focus on accuracy and efficiency, Hepta AI aims to streamline the research process for scientists and researchers, providing valuable insights and data visualization. The tool offers a user-friendly interface and advanced AI algorithms to deliver precise and reliable statistical outcomes.

Dimensions AI is an advanced scientific research database that provides a suite of research applications and time-saving solutions for intelligent discovery and faster insight. It hosts the largest collection of interconnected global research data, including publications, clinical trials, patents, policy documents, grants, datasets, and online citations. The platform offers easy-to-understand visualizations, purpose-built applications, and integrated AI technology to speed up research interpretation and analysis. Dimensions is designed to propel research by connecting the dots across the research ecosystem and saving researchers hours of time.

Chat-docs AI is an innovative AI application that allows users to interact with PDF documents through natural language conversations. The tool leverages advanced artificial intelligence algorithms to summarize long documents, explain complex concepts, and find key information with cited sources in seconds. It transforms PDFs into intelligent entities capable of dialogue, making learning, research, and analysis more interactive and personalized. Chat-docs AI is designed to be intuitive, secure, and accessible to users from various backgrounds, revolutionizing the way individuals engage with textual content.

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.

Seamless is an AI literature review tool designed for scientific research, enabling users to draft literature reviews 100x faster by leveraging advanced AI technology. The tool allows researchers to input a paper description, which Seamless uses to generate a literature review grounded on real papers from the Semantic Scholar database. With a user-friendly interface and access to a vast array of scientific works, Seamless streamlines the process of literature review creation, making it an indispensable tool for students and professionals across various fields.

SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem, including: * Benchmarks of equation solver implementations * Speed and robustness comparisons of methods for parameter estimation / inverse problems * Training universal differential equations (and subsets like neural ODEs) * Training of physics-informed neural networks (PINNs) * Surrogate comparisons, including radial basis functions, neural operators (DeepONets, Fourier Neural Operators), and more The SciML Bench suite is made to be a comprehensive open source benchmark from the ground up, covering the methods of computational science and scientific computing all the way to AI for science.

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.

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.

COMFYUI LLM PARTY is a node library designed for LLM workflow development in ComfyUI, an extremely minimalist UI interface primarily used for AI drawing and SD model-based workflows. The project aims to provide a complete set of nodes for constructing LLM workflows, enabling users to easily integrate them into existing SD workflows. It features various functionalities such as API integration, local large model integration, RAG support, code interpreters, online queries, conditional statements, looping links for large models, persona mask attachment, and tool invocations for weather lookup, time lookup, knowledge base, code execution, web search, and single-page search. Users can rapidly develop web applications using API + Streamlit and utilize LLM as a tool node. Additionally, the project includes an omnipotent interpreter node that allows the large model to perform any task, with recommendations to use the 'show_text' node for display output.

LaTeX2AI is a plugin for Adobe Illustrator that allows users to use editable text labels typeset in LaTeX inside an Illustrator document. It provides a seamless integration of LaTeX functionality within the Illustrator environment, enabling users to create and edit LaTeX labels, manage item scaling behavior, set global options, and save documents as PDF with included LaTeX labels. The tool simplifies the process of including LaTeX-generated content in Illustrator designs, ensuring accurate scaling and alignment with other elements in the document.

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 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.

Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

Cool-GenAI-Fashion-Papers is a curated list of resources related to GenAI-Fashion, including papers, workshops, companies, and products. It covers a wide range of topics such as fashion design synthesis, outfit recommendation, fashion knowledge extraction, trend analysis, and more. The repository provides valuable insights and resources for researchers, industry professionals, and enthusiasts interested in the intersection of AI and fashion.

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

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.

LLM4Opt is a collection of references and papers focusing on applying Large Language Models (LLMs) for diverse optimization tasks. The repository includes research papers, tutorials, workshops, competitions, and related collections related to LLMs in optimization. It covers a wide range of topics such as algorithm search, code generation, machine learning, science, industry, and more. The goal is to provide a comprehensive resource for researchers and practitioners interested in leveraging LLMs for optimization tasks.

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.

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.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

Qlib is an open-source, AI-oriented quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It covers the entire chain of quantitative investment, from alpha seeking to order execution. The platform empowers researchers to explore ideas and implement productions using AI technologies in quantitative investment. Qlib collaboratively solves key challenges in quantitative investment by releasing state-of-the-art research works in various paradigms. It provides a full ML pipeline for data processing, model training, and back-testing, enabling users to perform tasks such as forecasting market patterns, adapting to market dynamics, and modeling continuous investment decisions.

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.

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 'awesome-mobile-robotics' repository is a curated list of important content related to Mobile Robotics and AI. It includes resources such as courses, books, datasets, software and libraries, podcasts, conferences, journals, companies and jobs, laboratories and research groups, and miscellaneous resources. The repository covers a wide range of topics in the field of Mobile Robotics and AI, providing valuable information for enthusiasts, researchers, and professionals in the domain.

Expert in UFO/UAP analysis, employing scientific methods for realistic interpretations.

Expert in medical article analysis and review writing.

Professional medical manuscript editing and refining tool.

Expert in solving physics-related problems with clarity.

Translation of scientific publications in several languages in the field of generative AI, Machine Learning, and Deep Learning.

A precise and reliable scientific calculator using Python for complex math operations.

Scientific expert on humidity, providing detailed and informative guidance.

Sarcastic wit and Scientific genius.

Refines scientific economics papers with an eye for discipline-specific style and grammar.

Expert in scientific research grants, answers in Japanese with detailed references and citations.

Generates research hypotheses in various fields, ensuring scientific plausibility.

Crea hilos de tweets académicos y científicos

将论文、科技文章翻译成简体中文

Edits texts in physics and biology with scholarly precision

Helps write and refine medical SCI papers with accuracy and research guidance.

英翻中，适合于科技类文章，保留原汁原味，信雅达

Formal and academic Mandarin writing assistant with an IEEE focus.

Expert in SCLC research, focused on a specific paper and broader SCLC knowledge.

A Specialized Biochemistry and Pharmaceutical Research Assistant

Expert in ARTIQ Python coding, troubleshooting, learning and NDSPs.