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Replicate is an AI tool that allows users to run and fine-tune open-source models, deploy custom models at scale, and generate images, text, videos, music, and speech with just one line of code. It provides a platform for the community to contribute and explore thousands of production-ready AI models, enabling users to push the boundaries of AI beyond academic papers and demos. With features like fine-tuning models, deploying custom models, and scaling on Replicate, users can easily create and deploy AI solutions for various tasks.

4'33" is an AI agent designed to help students and researchers discover the people they need, such as students seeking professors in a specific field or city. The tool assists in asking better questions, connecting with individuals, and evaluating how well they align with the user's requirements and background. Powered by Perplexity, 4'33" offers a platform for connecting people and answering questions, alongside AI technology. The tool aims to facilitate easier and faster connections between users and relevant individuals, enabling knowledge sharing and collaboration.

Heartspace is an AI tool that provides high-quality automated content creation and personalized writing services. It offers features such as AI writing, smart content transformation, real-time collaboration, and AI-powered co-writing. Heartspace's AI tool, NirvanaAI, helps users stay updated with current events, create thought leadership content, and generate industry insights. The tool ensures GDPR compliance, EU data storage, and ethical communication practices.

RejuveAI is a decentralized token-based system that aims to democratize longevity globally. The Longevity App allows users to monitor essential health metrics, enhance lifespan, and earn RJV tokens. The application leverages revolutionary AI technology to analyze human body functions in-depth, providing insights for aging combat. RejuveAI collaborates with researchers, clinics, and data enthusiasts to ensure innovative outcomes are affordable and accessible. The platform also offers exclusive discounts on travel, supplements, medical tests, and longevity therapies.

GitHub is a collaborative platform for building and shipping software that offers various features such as GitHub Copilot for AI-powered coding assistance, security tools for finding and fixing vulnerabilities, automation of workflows, instant development environments, project management, code review, and collaboration tools. It aims to simplify the software development process and improve developer productivity by leveraging AI technology.

IX Coach is an AI-powered interdisciplinary coaching platform that helps individuals and teams achieve their goals. The platform provides users with access to a network of certified coaches, as well as a variety of tools and resources to support their coaching journey.

Almaya is a digital autobiography platform that allows users to record and share their stories, advice, and life lessons with their loved ones. It is a safe and private way to preserve memories and connect with family and friends, both now and in the future. Almaya uses artificial intelligence to help users create a personalized and interactive autobiography that can be easily shared and accessed from anywhere, anytime.

Emerge AI is an AI-driven wellness application that offers a unique experience by providing AI-generated digital companions to support users on their wellness journey. Through innovative NFT technology, users can earn tokens by achieving fitness milestones, contributing to the growth of their digital pets. The app also focuses on networking with friends to create a vibrant community around wellness and technology. With a comprehensive suite of features, Emerge AI aims to empower users in achieving wellness excellence.

Neurochain AI is a decentralized AI-as-a-Service (DeAIAS) network that provides an innovative solution for building, launching, and using AI-powered decentralized applications (dApps). It offers a community-driven approach to AI development, incentivizing contributors with $NCN rewards. The platform aims to address challenges in the centralized AI landscape by democratizing AI development and leveraging global computing resources. Neurochain AI also features a community-powered content generation engine and is developing its own independent blockchain. The team behind Neurochain AI includes experienced professionals in infrastructure, cryptography, computer science, and AI research.

Pl@ntNet is a citizen science project available as an application that helps you identify plants from your photos. It is a collaborative project that brings together scientists, naturalists, and citizens from all over the world to collect and share data on plant diversity. The app uses artificial intelligence to identify plants from photos, and the data collected is used to create a global database of plant diversity. Pl@ntNet is free to use and is available in over 20 languages.

Sarvam AI is an AI application focused on leading transformative research in AI to develop, deploy, and distribute Generative AI applications in India. The platform aims to build efficient large language models for India's diverse linguistic culture and enable new GenAI applications through bespoke enterprise models. Sarvam AI is also developing an enterprise-grade platform for developing and evaluating GenAI apps, while contributing to open-source models and datasets to accelerate AI innovation.

Quick, Draw! is a game built with machine learning. You draw, and a neural network tries to guess what you're drawing. Of course, it doesn't always work. But the more you play with it, the more it will learn. So far we have trained it on a few hundred concepts, and we hope to add more over time. We made this as an example of how you can use machine learning in fun ways.

The AI SDK is a free open-source library designed to empower developers to build AI-powered products. It offers a unified Provider API, allowing users to easily switch between AI providers with a single line of code. The SDK enables the creation of dynamic, AI-powered user interfaces and supports various frameworks like React, Next, Vue, Nuxt, and SvelteKit. It also provides the ability to stream AI responses instantly, enhancing user experience. The AI SDK has received high praise from developers for its ease of use, speed of development, and comprehensive documentation.

The Allen Institute for AI (AI2) is a leading research institute dedicated to advancing artificial intelligence technologies for the common good. They focus on Natural Language Processing, Computer Vision, and AI applications for the environment. AI2 collaborates with diverse teams to tackle challenging problems in AI research, aiming to create world-changing AI solutions. The institute promotes diversity, equity, and inclusion in the research community, and offers opportunities for individuals to contribute to impactful AI projects.

ONNX is an open standard for machine learning interoperability, providing a common format to represent machine learning models. It defines a set of operators and a file format for AI developers to use models across various frameworks, tools, runtimes, and compilers. ONNX promotes interoperability, hardware access, and community engagement.

AIhub is a platform that connects the AI community and the world by providing news articles, opinions, and education related to artificial intelligence. It serves as a hub for sharing information, resources, and contributing to the advancement of AI technologies. The platform covers a wide range of topics such as AI research, machine learning, robotics, and the societal impact of AI.

Flora Incognita is an AI-supported plant identification application that allows users to identify over 30,000 plant species. It enables users to save plant observations, access extensive plant fact sheets, and contribute to science through citizen science projects. The app is free of charge, ad-free, and works offline, making it ideal for educational purposes and nature conservation initiatives. The research project 'Flora Incognita++' combines AI technology with citizen science to enhance plant identification accuracy.

Comfy Org is an open-source AI tooling platform dedicated to advancing and democratizing AI technology. The platform offers tools like node manager, node registry, CLI, automated testing, and public documentation to support the ComfyUI ecosystem. Comfy Org aims to make state-of-the-art AI models accessible to a wider audience by fostering an open-source and community-driven approach. The team behind Comfy Org consists of individuals passionate about developing and maintaining various components of the platform, ensuring a reliable and secure environment for users to explore and contribute to AI tooling.

EcoSnap is an AI tool designed to help users recycle plastic more effectively. By simply taking a picture of a plastic code, users can learn how to recycle the item properly. The tool aims to promote environmental sustainability by providing accurate recycling information based on artificial intelligence technology. EcoSnap is user-friendly and accessible, making it convenient for individuals looking to contribute to a greener planet.

The website focuses on the DARROW project, which aims to make wastewater treatment more sustainable and efficient using a data-driven AI solution. It brings together experts from various disciplines to optimize resource recovery from wastewater, reduce energy consumption, and contribute to a circular economy. The project utilizes AI to enhance operational efficiency in wastewater treatment plants and explores innovative solutions for cleaner water management.

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

This repository is dedicated to enhancing Language Model (LLM) reasoning with reinforcement learning (RL). It includes a collection of the latest papers, slides, and materials related to RL-based LLM reasoning, aiming to facilitate quick learning and understanding in this field. Starring this repository allows users to stay updated and engaged with the forefront of RL-based LLM reasoning.

Academic_LLM_Sec_Papers is a curated collection of academic papers related to LLM Security Application. The repository includes papers sorted by conference name and published year, covering topics such as large language models for blockchain security, software engineering, machine learning, and more. Developers and researchers are welcome to contribute additional published papers to the list. The repository also provides information on listed conferences and journals related to security, networking, software engineering, and cryptography. The papers cover a wide range of topics including privacy risks, ethical concerns, vulnerabilities, threat modeling, code analysis, fuzzing, and more.

AI for Science paper collection is an initiative by AI for Science Community to collect and categorize papers in AI for Science areas by subjects, years, venues, and keywords. The repository contains `.csv` files with paper lists labeled by keys such as `Title`, `Conference`, `Type`, `Application`, `MLTech`, `OpenReviewLink`. It covers top conferences like ICML, NeurIPS, and ICLR. Volunteers can contribute by updating existing `.csv` files or adding new ones for uncovered conferences/years. The initiative aims to track the increasing trend of AI for Science papers and analyze trends in different applications.

WritingAIPaper is a comprehensive guide for beginners on crafting AI conference papers. It covers topics like paper structure, core ideas, framework construction, result analysis, and introduction writing. The guide aims to help novices navigate the complexities of academic writing and contribute to the field with clarity and confidence. It also provides tips on readability improvement, logical strength, defensibility, confusion time reduction, and information density increase. The appendix includes sections on AI paper production, a checklist for final hours, common negative review comments, and advice on dealing with paper rejection.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.

Awesome-LLM-in-Social-Science is a repository that compiles papers evaluating Large Language Models (LLMs) from a social science perspective. It includes papers on evaluating, aligning, and simulating LLMs, as well as enhancing tools in social science research. The repository categorizes papers based on their focus on attitudes, opinions, values, personality, morality, and more. It aims to contribute to discussions on the potential and challenges of using LLMs in social science research.

AI Deadlines is a web app that displays submission deadlines for top AI conferences like NeurIPS and ICLR. It helps researchers know when to submit their papers. The data is fetched from a GitHub repository and updated automatically using a CRON job. The project is based on an existing repository and features a new UI. Users can contribute by updating conference deadlines in the provided YAML file. The app can be run locally with Node.js and npm or deployed using Docker. It is built with Vite, TypeScript, React, shadcn-ui, and Tailwind CSS. The project is licensed under MIT.

This repository, Awesome-LLM-Survey, serves as a comprehensive collection of surveys related to Large Language Models (LLM). It covers various aspects of LLM, including instruction tuning, human alignment, LLM agents, hallucination, multi-modal capabilities, and more. Researchers are encouraged to contribute by updating information on their papers to benefit the LLM survey community.

Open Life Science AI: Medical Reasoning Tasks is a collaborative hub for developing cutting-edge reasoning tasks for Large Language Models (LLMs) in the medical, healthcare, and clinical domains. The repository aims to advance AI capabilities in healthcare by fostering accurate diagnoses, personalized treatments, and improved patient outcomes. It offers a diverse range of medical reasoning challenges such as Diagnostic Reasoning, Treatment Planning, Medical Image Analysis, Clinical Data Interpretation, Patient History Analysis, Ethical Decision Making, Medical Literature Comprehension, and Drug Interaction Assessment. Contributors can join the community of healthcare professionals, AI researchers, and enthusiasts to contribute to the repository by creating new tasks or improvements following the provided guidelines. The repository also provides resources including a task list, evaluation metrics, medical AI papers, and healthcare datasets for training and evaluation.

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.

The 'LLMs-in-science' repository is a collaborative environment for organizing papers related to large language models (LLMs) and autonomous agents in the field of chemistry. The goal is to discuss trend topics, challenges, and the potential for supporting scientific discovery in the context of artificial intelligence. The repository aims to maintain a systematic structure of the field and welcomes contributions from the community to keep the content up-to-date and relevant.

PDFMathTranslate is a tool designed for translating scientific papers and conducting bilingual comparisons. It preserves formulas, charts, table of contents, and annotations. The tool supports multiple languages and diverse translation services. It provides a command-line tool, interactive user interface, and Docker deployment. Users can try the application through online demos. The tool offers various installation methods including command-line, portable, graphic user interface, and Docker. Advanced options allow users to customize translation settings. Additionally, the tool supports secondary development through APIs for Python and HTTP. Future plans include parsing layout with DocLayNet based models, fixing page rotation and format issues, supporting non-PDF/A files, and integrating plugins for Zotero and Obsidian.

The 'LLM-Brained-GUI-Agents-Survey' repository contains code for a searchable paper page and assets used in the survey paper on Large Language Model-Brained GUI Agents. These agents operate within GUI environments, utilizing Large Language Models as their core inference and cognitive engine to generate, plan, and execute actions flexibly and adaptively. The repository also encourages contributions from the community for new papers, resources, or improvements related to LLM-Powered GUI Agents.

This repository compiles a list of academic papers that evaluate, align, simulate, and provide surveys or perspectives on the use of Large Language Models (LLMs) in the field of Social Science. The papers cover various aspects of LLM research, including assessing their alignment with human values, evaluating their capabilities in tasks such as opinion formation and moral reasoning, and exploring their potential for simulating social interactions and addressing issues in diverse fields of Social Science. The repository aims to provide a comprehensive resource for researchers and practitioners interested in the intersection of LLMs and Social Science.

LLM Agents Papers is a repository containing must-read papers on Large Language Model Agents. It covers a wide range of topics related to language model agents, including interactive natural language processing, large language model-based autonomous agents, personality traits in large language models, memory enhancements, planning capabilities, tool use, multi-agent communication, and more. The repository also provides resources such as benchmarks, types of tools, and a tool list for building and evaluating language model agents. Contributors are encouraged to add important works to the repository.

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.

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