Best AI tools for< Find Relevant Papers >

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.

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.

Seamless is an AI literature review tool designed for scientific research. It allows researchers to draft literature reviews 100 times faster by leveraging advanced AI technology. The tool finds relevant papers and creates a draft directly from the user's work excerpt. Seamless is used by over 20,000 students and researchers worldwide, providing lightning-fast access to scientific databases and revolutionizing the creation of literature reviews.

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.

Emergent Mind is a website that provides access to trending AI papers. Users can browse papers by category, week, month, or year. The website also provides summaries of trending AI papers on Twitter.

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.

PaperLens is an AI-powered platform that serves as a lens into the world of research papers. It allows users to search through research papers using natural language or verify scientific claims with supporting evidence. The platform combines cutting-edge AI technology with intuitive design to help users find the most relevant academic research. PaperLens leverages state-of-the-art RAG (Retrieval-Augmented Generation) technology for precise, real-time results. Users can find relevant research papers based on meaning and context, filter results by publication date and relevance score, and benefit from simple, transparent pricing plans.

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.

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

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.

Sourcely is an AI-powered academic search assistant that helps students and researchers find, summarize, and add credible academic sources efficiently. With access to over 200 million research papers and advanced search filters, Sourcely streamlines the research process by finding sources, summarizing them, and exporting citations instantly. It simplifies source discovery, offers targeted citations, free PDF downloads, and a citations library for easy organization. Users can save time by getting credible summaries, exporting references in various formats, and applying advanced filters for tailored source discovery. Sourcely is a valuable tool for academic writing, research papers, theses, and essays, automating the search for appropriate citations and saving valuable time and energy.

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.

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

Jobright is an AI-powered job search platform that acts as your co-pilot in finding the freshest job opportunities. With its advanced AI technology, Jobright scans the job market continuously to bring you up-to-date job listings, saving you time and effort in your job search. The platform matches jobs to your skills and experience, provides key company insights, and suggests resume tweaks to help you secure more interviews with the right employers. Jobright offers a wide range of job listings across various industries, making it a valuable tool for job seekers looking to stay ahead in their job search.

Octolens is an AI social listening tool that helps monitor keyword mentions on various social and community platforms. It provides real-time notifications for mentions on platforms like Twitter, LinkedIn, GitHub, and more. The tool uses AI to track conversations, complaints, and requests related to your product category, enabling businesses to engage with their audience effectively and stay informed about relevant discussions online.

GovDash is an AI-powered platform designed for government contractors to streamline the proposal development process, manage contracts, and identify opportunities efficiently. It offers features such as automated compliance shredding, personalized recommendations, and review assistance to enhance bid quality and save time. GovDash is trusted by hundreds of capture and proposal teams to improve business development effectiveness and productivity. The platform integrates with existing tools like Microsoft Word and Salesforce, ensuring seamless workflow for users in the government contracting space.

The 'YouTube Comment Finder And AI Analysis' is a comprehensive web-based tool designed to simplify the process of searching, filtering, managing, and analyzing comments on YouTube videos. It empowers users to search, filter, sort, and analyze comments with ease, leveraging AI-powered comment analysis to gain insights into sentiment, trending topics, key points, and concise summaries of comments. The tool offers features such as comment search, filtering, sorting, exporting, and random comment picking, making it a valuable asset for content creators, marketers, and individuals looking to navigate the vast sea of comments on YouTube videos.

Nichely is an AI-powered SEO tool that helps users dominate their niche by utilizing cutting-edge AI technology to navigate and correlate millions of topics in various niches. It offers features such as topic discovery, topic research, and keyword research to assist users in building detailed topical maps and comprehensive topic clusters. With Nichely, users can uncover untapped content opportunities, find relevant long-tail keywords, and analyze SERPs. The tool is designed for content/niche website owners, entrepreneurs, and individuals looking to improve their topical authority and construct strong topical clusters and maps.

Name Drop AI is a tool that helps businesses generate leads and grow organically by identifying relevant conversations on social media platforms such as Twitter, Reddit, and others. It uses AI to pinpoint the most relevant conversations for a business's product or service, allowing them to engage with potential customers in a more authentic and efficient way. With Name Drop AI, businesses can save time and money by focusing on the conversations that matter most and interact with their audience in a more personalized manner.

Excire is an award-winning AI-based software designed for perfect photo management. The latest version, Excire Foto 2024, elevates your photo search and organization to a new level. It features five independent AI models that provide various search functions. Additionally, it offers innovative features and enhanced performance. Excire Search 2024 is the latest upgrade for Lightroom Classic users, offering intelligent image management, improved photo analysis AI, and integrated free-text search. Excire excels in assisting users in maintaining digital archives, finding photos quickly, and creating photo collections effortlessly.

Lobe Chat Plugins Index is a repository that serves as a collection of various plugins for Function Calling. Users can submit their plugins by following specific instructions. The repository includes a wide range of plugins for different tasks such as image generation, stock analysis, web search, NFT tracking, calendar management, and more. Each plugin is tagged with relevant keywords for easy identification and usage. The repository encourages contributions and provides guidelines for submitting new plugins. It is a valuable resource for developers looking to enhance chatbot functionalities with different plugins.

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.

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.

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.

Welcome to the comprehensive collection of advanced + agentic Retrieval-Augmented Generation (RAG) techniques. This repository covers the most effective advanced + agentic RAG techniques with clear implementations and explanations. It aims to provide a helpful resource for researchers and developers looking to use advanced RAG techniques in their projects, offering ready-to-use implementations and guidance on evaluation methods. The RAG framework addresses limitations of Large Language Models by using external documents for in-context learning, ensuring contextually relevant and accurate responses. The repository includes detailed descriptions of various RAG techniques, tools used, and implementation guidance for each technique.

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 follows a process of embedding docs and queries, searching for top passages, creating summaries, scoring and selecting relevant summaries, putting summaries into prompt, and generating answers. Users can customize prompts and use various models for embeddings and LLMs. The tool can be used asynchronously and supports adding documents from paths, files, or URLs.

Perplexica is an open-source AI-powered search engine that utilizes advanced machine learning algorithms to provide clear answers with sources cited. It offers various modes like Copilot Mode, Normal Mode, and Focus Modes for specific types of questions. Perplexica ensures up-to-date information by using SearxNG metasearch engine. It also features image and video search capabilities and upcoming features include finalizing Copilot Mode and adding Discover and History Saving features.

Cleanlab helps you **clean** data and **lab** els by automatically detecting issues in a ML dataset. To facilitate **machine learning with messy, real-world data** , this data-centric AI package uses your _existing_ models to estimate dataset problems that can be fixed to train even _better_ models.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

TokenFormer is a fully attention-based neural network architecture that leverages tokenized model parameters to enhance architectural flexibility. It aims to maximize the flexibility of neural networks by unifying token-token and token-parameter interactions through the attention mechanism. The architecture allows for incremental model scaling and has shown promising results in language modeling and visual modeling tasks. The codebase is clean, concise, easily readable, state-of-the-art, and relies on minimal dependencies.

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

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 'llm-misinformation-survey' repository is dedicated to the survey on combating misinformation in the age of Large Language Models (LLMs). It explores the opportunities and challenges of utilizing LLMs to combat misinformation, providing insights into the history of combating misinformation, current efforts, and future outlook. The repository serves as a resource hub for the initiative 'LLMs Meet Misinformation' and welcomes contributions of relevant research papers and resources. The goal is to facilitate interdisciplinary efforts in combating LLM-generated misinformation and promoting the responsible use of LLMs in fighting misinformation.

Awesome-Robotics-3D is a curated list of 3D Vision papers related to Robotics domain, focusing on large models like LLMs/VLMs. It includes papers on Policy Learning, Pretraining, VLM and LLM, Representations, and Simulations, Datasets, and Benchmarks. The repository is maintained by Zubair Irshad and welcomes contributions and suggestions for adding papers. It serves as a valuable resource for researchers and practitioners in the field of Robotics and Computer Vision.

This repository is a curated list of awesome large AI models in audio signal processing, focusing on the application of large language models to audio tasks. It includes survey papers, popular large audio models, automatic speech recognition, neural speech synthesis, speech translation, other speech applications, large audio models in music, and audio datasets. The repository aims to provide a comprehensive overview of recent advancements and challenges in applying large language models to audio signal processing, showcasing the efficacy of transformer-based architectures in various audio tasks.

RTL-Coder is a tool designed to outperform GPT-3.5 in RTL code generation by providing a fully open-source dataset and a lightweight solution. It targets Verilog code generation and offers an automated flow to generate a large labeled dataset with over 27,000 diverse Verilog design problems and answers. The tool addresses the data availability challenge in IC design-related tasks and can be used for various applications beyond LLMs. The tool includes four RTL code generation models available on the HuggingFace platform, each with specific features and performance characteristics. Additionally, RTL-Coder introduces a new LLM training scheme based on code quality feedback to further enhance model performance and reduce GPU memory consumption.

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

Cellm is an Excel extension that allows users to leverage Large Language Models (LLMs) like ChatGPT within cell formulas. It enables users to extract AI responses to text ranges, making it useful for automating repetitive tasks that involve data processing and analysis. Cellm supports various models from Anthropic, Mistral, OpenAI, and Google, as well as locally hosted models via Llamafiles, Ollama, or vLLM. The tool is designed to simplify the integration of AI capabilities into Excel for tasks such as text classification, data cleaning, content summarization, entity extraction, and more.

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

Deep learning researcher explaining Google Gemini from PDFs.

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Getting ready to query agents or publishers? Upload your manuscript. I analyse your novel's writing style, themes and genre. I'll tell you how it's relevant to a modern audience, offer marketing insights and will even write you a draft synopsis and cover letter. I'll help you find relevant agents.

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I suggest trending hashtags for social media posts based on content and platform.

Teaches you how to use the Metaphor Search API using our Python SDK

Analytical and encouraging literature review assistant.

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Extract insights seamlessly from diverse documents.

Finds the relevant XKCD comic for the described scenario

Web-savvy assistant for finding relevant scholarships

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Effortlessly suggests relevant hashtags for Instagram, LinkedIn, Twitter, and Facebook posts.

This Assistant assists library catalogers in selecting authority records. It advises librarians in creating queries and selecting the most relevant Name and Subject Heading Authority Records.

Write extended documentary scripts with free relevant video, music & thumbnail.

An AI blending wisdom with short, relevant myths.

Compares Your Resume with a Job Description, Highlighting Relevant Skills and Experience, and Finding Gaps. Provides Example Interview Questions. 👩‍💻 #Career #Jobhunting #Hiring #Hunting #Search #AISalon

An educational guide for respiratory therapists, covering a wide range of relevant topics.

Creates creative Twitter search queries about any topic or person