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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.

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.

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.

The website focuses on groundbreaking research and studies across various scientific fields, including quantum communication, semiconductor dynamics, mental health support, dietary interventions, computer vision, autonomous systems safety, machine learning applications, and astrophysical observations. It covers innovative findings, theoretical studies, and technological advancements that have the potential to reshape industries and scientific understanding.

EleutherAI is an open-source AI research platform that focuses on discussing and disseminating cutting-edge research in the field of artificial intelligence. The platform provides updates on various research projects, including Mechanistic Anomaly Detection, Automated Interpretability for Sparse Autoencoder Features, Experiments in Generalization, Concept Erasure, Knowledge Elicitation, and more. EleutherAI aims to foster collaboration and innovation in the AI community by sharing insights and advancements in the field.

ScienceCast is a platform that enhances scientific papers with interactive media, providing a unique way to explore and engage with research articles in various fields such as Biology, Computer Science, Economics, Electrical Engineering, Mathematics, Physics, and more. Users can access a wide range of featured casts, including topics like cancer biology, genomics, immunology, microbiology, molecular biology, biochemistry, and bioinformatics. The platform aims to make complex scientific information more accessible and engaging for researchers and enthusiasts alike.

TextLayer is an AI-powered research companion that simplifies access to the latest research in machine learning. It empowers users to turn new discoveries into powerful solutions by providing personalized recommendations, AI-generated insights, and implementation support. The platform offers curated AI-generated summaries of research papers, tailored recommendations, and a chat integration for interacting with AI. TextLayer aims to bridge the gap between complex ML research papers and understanding, fostering curiosity, innovation, and shaping the future of Artificial Intelligence.

AI News is a website dedicated to providing news, analysis, and insights related to artificial intelligence (AI) technologies. The site covers a wide range of topics within the AI domain, including applications, chatbots, face recognition, virtual assistants, voice recognition, companies like Amazon, Apple, Google, and Microsoft, as well as deep learning, ethics, industries, machine learning, robotics, security, and more. AI News aims to keep readers informed about the latest developments, trends, and innovations in the field of artificial intelligence.

The website is a platform managed by Dr. Elie Bursztein, the Google & DeepMind AI Cybersecurity technical and research lead. It features a collection of publications, blog posts, talks, and press releases related to cybersecurity, artificial intelligence, and technology. Dr. Bursztein shares insights and research findings on various topics such as secure AI workflows, language models in cybersecurity, hate and harassment online, and more. Visitors can explore recent content and subscribe to receive cutting-edge research directly in their inbox.

La Biblia de la IA - The Bible of AI™ Journal is an educational research platform focused on Artificial Intelligence. It provides in-depth analysis, articles, and discussions on various AI-related topics, aiming to advance knowledge and understanding in the field of AI. The platform covers a wide range of subjects, from machine learning algorithms to ethical considerations in AI development.

Ledge.ai is an AI application that focuses on the latest trends in artificial intelligence. The platform provides articles, videos, and solutions related to various fields such as business, learning, engineering, academics & study, public, entertainment & art. Users can stay updated on AI developments, including new models like GPT-4o and multi-modal AI. Ledge.ai covers a wide range of topics from OpenAI announcements to academic research and industry applications of AI technology.

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.

AIM Research is a leading platform providing insights and analysis on the Artificial Intelligence industry. The website offers a comprehensive range of resources, including research reports, event coverage, news articles, and expert opinions. AIM Research focuses on highlighting the latest trends, innovations, and key players in the AI sector, catering to professionals, researchers, and enthusiasts seeking in-depth knowledge and understanding of AI technologies and applications.

Google DeepMind is a British artificial intelligence research laboratory owned by Google. The company was founded in 2010 by Demis Hassabis, Shane Legg, and Mustafa Suleyman. DeepMind's mission is to develop safe and beneficial artificial intelligence. The company's research focuses on a variety of topics, including machine learning, reinforcement learning, and computer vision. DeepMind has made significant contributions to the field of artificial intelligence, including the development of AlphaGo, the first computer program to defeat a professional human Go player.

Ivie is an AI-powered user research tool that automates the collection and analysis of qualitative user insights to help product teams build better products. It offers features such as AI-powered insights, processed user insights, in-depth analysis, automated follow-up questions, multilingual support, and more. Ivie provides advantages like human-like conversations, scalable surveys, customizable AI researchers, quick research setup, and multiple question types. However, it has disadvantages such as limited customization options, potential language barriers, and the need for user training. The frequently asked questions cover topics like supported research types, data security, multilingual research, and research findings presentation. Ivie is suitable for jobs related to user research, product development, customer satisfaction analysis, market research, and concept testing. The application can be used for tasks like conducting customer interviews, analyzing user feedback, creating surveys, synthesizing research findings, and building user personas.

Qonqur is a cutting-edge XR (Extended Reality) platform that offers a new paradigm in learning and knowledge exploration. It provides users with the ability to learn faster, connect ideas with ease, and delve into the frontiers of knowledge through its brilliant Virtual AI Companion. Qonqur aims to revolutionize mixed reality experiences by offering fluid and flawless interactions with various types of content, including documents, videos, websites, 3D models, and code. The platform is designed to liberate intellect and creativity from all limitations, blending arts with sciences to create a new horizon in XR technology.

Albus is an AI-powered platform that allows users to explore, learn, and create with the help of advanced AI technologies. It offers features such as image generation with SDXL and DALL-E 3, PDF intelligence, image/audio insights, and more. Users can access a wide range of AI models and tools to enhance their creative and learning processes. Albus aims to streamline the generation of ideas and insights by leveraging AI capabilities while still valuing human creativity and intelligence.

Kavout is an AI-powered financial research assistant that provides investors with data-driven insights and cutting-edge technology to help them make informed investment decisions. The platform offers a range of features, including natural language search, stock screening, portfolio analysis, and personalized recommendations. Kavout's AI algorithms adapt to each user's unique investment style, providing tailored insights and guidance.

Ad-Free AI Chat is an Android app available in the Play Store. It offers ad-free GPT voice chat, games, language learning, and research assistance. Users can create their own commands to automate tasks and use the app with Android Auto. The app supports ChatGPT 4, ChatGPT 3.5, and Google Gemini Pro.

Etherpal.xyz is a website that is currently for sale. It provides resources and information related to Etherpal. Users can find valuable content and details about Etherpal on this website, which can help them understand the platform better and make informed decisions.

The On-board Artificial Intelligence Research (OnAIR) Platform is a framework that enables AI algorithms written in Python to interact with NASA's cFS. It is intended to explore research concepts in autonomous operations in a simulated environment. The platform provides tools for generating environments, handling telemetry data through Redis, running unit tests, and contributing to the repository. Users can set up a conda environment, configure telemetry and Redis examples, run simulations, and conduct unit tests to ensure the functionality of their AI algorithms. The platform also includes guidelines for licensing, copyright, and contributions to the repository.

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.

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.

awesome-ml-blogs is a curated list of machine learning technical blogs covering a wide range of topics from research to deployment. It includes blogs from big corporations, MLOps startups, data labeling platforms, universities, community content, personal blogs, synthetic data providers, and more. The repository aims to help individuals stay updated with the latest research breakthroughs and practical tutorials in the field of machine learning.

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.

ShortcutsBench is a project focused on collecting and analyzing workflows created in the Shortcuts app, providing a dataset of shortcut metadata, source files, and API information. It aims to study the integration of large language models with Apple devices, particularly focusing on the role of shortcuts in enhancing user experience. The project offers insights for Shortcuts users, enthusiasts, and researchers to explore, customize workflows, and study automated workflows, low-code programming, and API-based agents.

Earth2Studio is a Python-based package designed to enable users to quickly get started with AI weather and climate models. It provides access to pre-trained models, diagnostic tools, data sources, IO utilities, perturbation methods, and sample workflows for building custom weather prediction workflows. The package aims to empower users to explore AI-driven meteorology through modular components and seamless integration with other Nvidia packages like Modulus.

VITA is an open-source interactive omni multimodal Large Language Model (LLM) capable of processing video, image, text, and audio inputs simultaneously. It stands out with features like Omni Multimodal Understanding, Non-awakening Interaction, and Audio Interrupt Interaction. VITA can respond to user queries without a wake-up word, track and filter external queries in real-time, and handle various query inputs effectively. The model utilizes state tokens and a duplex scheme to enhance the multimodal interactive experience.

MindSearch is an open-source AI Search Engine Framework that mimics human minds to provide deep AI search capabilities. It allows users to deploy their own search engine using either close-source or open-source language models. MindSearch offers features such as answering any question using web knowledge, in-depth knowledge discovery, detailed solution paths, optimized UI experience, and dynamic graph construction process.

Awesome LLM Apps is a curated collection of applications that leverage RAG with OpenAI, Anthropic, Gemini, and open-source models. The repository contains projects such as Local Llama-3 with RAG for chatting with webpages locally, Chat with Gmail for interacting with Gmail using natural language, Chat with Substack Newsletter for conversing with Substack newsletters using GPT-4, Chat with PDF for intelligent conversation based on PDF documents, and Chat with YouTube Videos for engaging with YouTube video content through natural language. Users can clone the repository, navigate to specific project directories, install dependencies, and follow project-specific instructions to set up and run the apps. Contributions are encouraged, and new app ideas or improvements can be submitted via pull requests.

This repository is a collection of papers on leveraging Large Language Models (LLMs) in Graph Tasks. It provides a comprehensive overview of how LLMs can enhance graph-related tasks by combining them with traditional Graph Neural Networks (GNNs). The integration of LLMs with GNNs allows for capturing both structural and contextual aspects of nodes in graph data, leading to more powerful graph learning. The repository includes summaries of various models that leverage LLMs to assist in graph-related tasks, along with links to papers and code repositories for further exploration.

Video-MME is the first-ever comprehensive evaluation benchmark of Multi-modal Large Language Models (MLLMs) in Video Analysis. It assesses the capabilities of MLLMs in processing video data, covering a wide range of visual domains, temporal durations, and data modalities. The dataset comprises 900 videos with 256 hours and 2,700 human-annotated question-answer pairs. It distinguishes itself through features like duration variety, diversity in video types, breadth in data modalities, and quality in annotations.

MathVerse is an all-around visual math benchmark designed to evaluate the capabilities of Multi-modal Large Language Models (MLLMs) in visual math problem-solving. It collects high-quality math problems with diagrams to assess how well MLLMs can understand visual diagrams for mathematical reasoning. The benchmark includes 2,612 problems transformed into six versions each, contributing to 15K test samples. It also introduces a Chain-of-Thought (CoT) Evaluation strategy for fine-grained assessment of output answers.

MME-RealWorld is a benchmark designed to address real-world applications with practical relevance, featuring 13,366 high-resolution images and 29,429 annotations across 43 tasks. It aims to provide substantial recognition challenges and overcome common barriers in existing Multimodal Large Language Model benchmarks, such as small data scale, restricted data quality, and insufficient task difficulty. The dataset offers advantages in data scale, data quality, task difficulty, and real-world utility compared to existing benchmarks. It also includes a Chinese version with additional images and QA pairs focused on Chinese scenarios.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

The Persian License Plate Recognition (PLPR) system is a state-of-the-art solution designed for detecting and recognizing Persian license plates in images and video streams. Leveraging advanced deep learning models and a user-friendly interface, it ensures reliable performance across different scenarios. The system offers advanced detection using YOLOv5 models, precise recognition of Persian characters, real-time processing capabilities, and a user-friendly GUI. It is well-suited for applications in traffic monitoring, automated vehicle identification, and similar fields. The system's architecture includes modules for resident management, entrance management, and a detailed flowchart explaining the process from system initialization to displaying results in the GUI. Hardware requirements include an Intel Core i5 processor, 8 GB RAM, a dedicated GPU with at least 4 GB VRAM, and an SSD with 20 GB of free space. The system can be installed by cloning the repository and installing required Python packages. Users can customize the video source for processing and run the application to upload and process images or video streams. The system's GUI allows for parameter adjustments to optimize performance, and the Wiki provides in-depth information on the system's architecture and model training.

ChatData is a robust chat-with-documents application designed to extract information and provide answers by querying the MyScale free knowledge base or uploaded documents. It leverages the Retrieval Augmented Generation (RAG) framework, millions of Wikipedia pages, and arXiv papers. Features include self-querying retriever, VectorSQL, session management, and building a personalized knowledge base. Users can effortlessly navigate vast data, explore academic papers, and research documents. ChatData empowers researchers, students, and knowledge enthusiasts to unlock the true potential of information retrieval.

Build-your-own-AI-Assistant-Solution-Accelerator is a pre-release and preview solution that helps users create their own AI assistants. It leverages Azure Open AI Service, Azure AI Search, and Microsoft Fabric to identify, summarize, and categorize unstructured information. Users can easily find relevant articles and grants, generate grant applications, and export them as PDF or Word documents. The solution accelerator provides reusable architecture and code snippets for building AI assistants with enterprise data. It is designed for researchers looking to explore flu vaccine studies and grants to accelerate grant proposal submissions.

Odyssey is a framework designed to empower agents with open-world skills in Minecraft. It provides an interactive agent with a skill library, a fine-tuned LLaMA-3 model, and an open-world benchmark for evaluating agent capabilities. The framework enables agents to explore diverse gameplay opportunities in the vast Minecraft world by offering primitive and compositional skills, extensive training data, and various long-term planning tasks. Odyssey aims to advance research on autonomous agent solutions by providing datasets, model weights, and code for public use.

fastRAG is a research framework designed to build and explore efficient retrieval-augmented generative models. It incorporates state-of-the-art Large Language Models (LLMs) and Information Retrieval to empower researchers and developers with a comprehensive tool-set for advancing retrieval augmented generation. The framework is optimized for Intel hardware, customizable, and includes key features such as optimized RAG pipelines, efficient components, and RAG-efficient components like ColBERT and Fusion-in-Decoder (FiD). fastRAG supports various unique components and backends for running LLMs, making it a versatile tool for research and development in the field of retrieval-augmented generation.

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