The `Call-for-Reviewers` repository aims to collect the latest 'call for reviewers' links from various top CS/ML/AI conferences/journals. It provides an opportunity for individuals in the computer/ machine learning/ artificial intelligence fields to gain review experience for applying for NIW/H1B/EB1 or enhancing their CV. The repository helps users stay updated with the latest research trends and engage with the academic community.

LLM-Agent-Survey is a comprehensive repository that provides a curated list of papers related to Large Language Model (LLM) agents. The repository categorizes papers based on LLM-Profiled Roles and includes high-quality publications from prestigious conferences and journals. It aims to offer a systematic understanding of LLM-based agents, covering topics such as tool use, planning, and feedback learning. The repository also includes unpublished papers with insightful analysis and novelty, marked for future updates. Users can explore a wide range of surveys, tool use cases, planning workflows, and benchmarks related to LLM agents.

Awesome deep logic is a curated list of papers and resources focusing on integrating symbolic logic into deep neural networks. It includes surveys, tutorials, and research papers that explore the intersection of logic and deep learning. The repository aims to provide valuable insights and knowledge on how logic can be used to enhance reasoning, knowledge regularization, weak supervision, and explainability in neural networks.

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

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.

This repository contains a curated list of **papers using Large Language/Multi-Modal Models for Robotics/RL**. Template from awesome-Implicit-NeRF-Robotics Please feel free to send me pull requests or email to add papers! If you find this repository useful, please consider citing and STARing this list. Feel free to share this list with others! ## Overview * Surveys * Reasoning * Planning * Manipulation * Instructions and Navigation * Simulation Frameworks * Citation

rLLM (relationLLM) is a Pytorch library for Relational Table Learning (RTL) with LLMs. It breaks down state-of-the-art GNNs, LLMs, and TNNs as standardized modules and facilitates novel model building in a 'combine, align, and co-train' way using these modules. The library is LLM-friendly, processes various graphs as multiple tables linked by foreign keys, introduces new relational table datasets, and is supported by students and teachers from Shanghai Jiao Tong University and Tsinghua University.

Awesome-TimeSeries-SpatioTemporal-LM-LLM is a curated list of Large (Language) Models and Foundation Models for Temporal Data, including Time Series, Spatio-temporal, and Event Data. The repository aims to summarize recent advances in Large Models and Foundation Models for Time Series and Spatio-Temporal Data with resources such as papers, code, and data. It covers various applications like General Time Series Analysis, Transportation, Finance, Healthcare, Event Analysis, Climate, Video Data, and more. The repository also includes related resources, surveys, and papers on Large Language Models, Foundation Models, and their applications in AIOps.

Aim is an open-source, self-hosted ML experiment tracking tool designed to handle 10,000s of training runs. Aim provides a performant and beautiful UI for exploring and comparing training runs. Additionally, its SDK enables programmatic access to tracked metadata — perfect for automations and Jupyter Notebook analysis. **Aim's mission is to democratize AI dev tools 🎯**

This repository is a comprehensive survey of harmful fine-tuning attacks and defenses for large language models (LLMs). It provides a curated list of must-read papers on the topic, covering various aspects such as alignment stage defenses, fine-tuning stage defenses, post-fine-tuning stage defenses, mechanical studies, benchmarks, and attacks/defenses for federated fine-tuning. The repository aims to keep researchers updated on the latest developments in the field and offers insights into the vulnerabilities and safeguards related to fine-tuning LLMs.

This repository focuses on exploring tools that enhance the performance of language models for various tasks. It provides a structured list of literature relevant to tool-augmented language models, covering topics such as tool basics, tool use paradigm, scenarios, advanced methods, and evaluation. The repository includes papers, preprints, and books that discuss the use of tools in conjunction with language models for tasks like reasoning, question answering, mathematical calculations, accessing knowledge, interacting with the world, and handling non-textual modalities.

This repository contains a collection of papers related to tool learning with large language models (LLMs). The papers are organized according to the survey paper 'Tool Learning with Large Language Models: A Survey'. The survey focuses on the benefits and implementation of tool learning with LLMs, covering aspects such as task planning, tool selection, tool calling, response generation, benchmarks, evaluation, challenges, and future directions in the field. It aims to provide a comprehensive understanding of tool learning with LLMs and inspire further exploration in this emerging area.

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 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.

The `Call-for-Reviewers` repository aims to collect the latest 'call for reviewers' links from various top CS/ML/AI conferences/journals. It provides an opportunity for individuals in the computer/ machine learning/ artificial intelligence fields to gain review experience for applying for NIW/H1B/EB1 or enhancing their CV. The repository helps users stay updated with the latest research trends and engage with the academic community.

LaVague is an open-source Large Action Model framework that uses advanced AI techniques to compile natural language instructions into browser automation code. It leverages Selenium or Playwright for browser actions. Users can interact with LaVague through an interactive Gradio interface to automate web interactions. The tool requires an OpenAI API key for default examples and offers a Playwright integration guide. Contributors can help by working on outlined tasks, submitting PRs, and engaging with the community on Discord. The project roadmap is available to track progress, but users should exercise caution when executing LLM-generated code using 'exec'.

Hacker-league is a tool designed for gaming enthusiasts and developers to explore and play with game development. It provides a platform for users to build games, experiment with graphics, and enhance their coding skills. The tool offers features such as gamepad support, Vulkan API integration, shader compilation, and community engagement through Discord and public development showcases. Users can easily install the tool on Debian-based systems and contribute to its development for broader platform compatibility.

Awesome-Lists is a curated index of selected resources spanning various fields including programming languages and theories, web and frontend development, server-side development and infrastructure, cloud computing and big data, data science and artificial intelligence, product design, etc. It includes articles, books, courses, examples, open-source projects, and more. The repository categorizes resources according to the knowledge system of different domains, aiming to provide valuable and concise material indexes for readers. Users can explore and learn from a wide range of high-quality resources in a systematic way.

Python Trending Weekly is a curated newsletter by Python猫 that selects the most valuable articles, tutorials, open-source projects, software tools, podcasts, videos, and hot topics from over 250 English and Chinese sources. The newsletter aims to help readers improve their Python skills and increase their income from both professional and side projects. It offers paid subscription options and is available on various platforms like GitHub, WeChat, blogs, email, Telegram, and Twitter. Each issue shares a collection of articles, open-source projects, videos, and books related to Python and technology.

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.

Free AI Tips is a GitHub repository that provides weekly tips on Generative AI and Machine Learning. Users can register to receive these tips for free. The repository aims to offer valuable insights and knowledge in the field of AI and ML to help individuals enhance their skills and stay updated with the latest trends and developments.

HuggingArxiv is a tool designed to push research papers related to large language models from Arxiv. It helps users stay updated with the latest developments in the field of large language models by providing notifications and access to relevant papers.

The ASReview project implements active learning for systematic reviews, utilizing AI-aided pipelines to assist in finding relevant texts for search tasks. It accelerates the screening of textual data with minimal human input, saving time and increasing output quality. The software offers three modes: Oracle for interactive screening, Exploration for teaching purposes, and Simulation for evaluating active learning models. ASReview LAB is designed to support decision-making in any discipline or industry by improving efficiency and transparency in screening large amounts of textual data.

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

The Classical Language Toolkit (CLTK) is a Python library that provides natural language processing (NLP) capabilities for pre-modern languages. It offers a modular processing pipeline with pre-configured defaults and supports almost 20 languages. Users can install the latest version using pip and access detailed documentation on the official website. The toolkit is designed to meet the unique needs of researchers working with historical languages, filling a void in the NLP landscape that often neglects non-spoken languages and different research goals.

The 'Conference-Acceptance-Rate' repository provides acceptance rates for top-tier AI-related conferences in the fields of Natural Language Processing, Computational Linguistics, Computer Vision, Pattern Recognition, Machine Learning, Learning Theory, Artificial Intelligence, Data Mining, Information Retrieval, Speech Processing, and Signal Processing. The data includes acceptance rates for long papers and short papers over several years for each conference, allowing researchers to track trends and make informed decisions about where to submit their work.

PDFToChat is a tool that allows users to chat with their PDF documents in seconds. It is powered by Together AI and Pinecone, utilizing a tech stack including Next.js, Mixtral, M2 Bert, LangChain.js, MongoDB Atlas, Bytescale, Vercel, Clerk, and Tailwind CSS. Users can deploy the tool to Vercel or any other host by setting up Together.ai, MongoDB Atlas database, Bytescale, Clerk, and Vercel. The tool enables users to interact with PDFs through chat, with future tasks including adding features like trash icon for deleting PDFs, exploring different embedding models, implementing auto scrolling, improving replies, benchmarking accuracy, researching chunking and retrieval best practices, adding demo video, upgrading to Next.js 14, adding analytics, customizing tailwind prose, saving chats in postgres DB, compressing large PDFs, implementing custom uploader, session tracking, error handling, and support for images in PDFs.

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

The `Call-for-Reviewers` repository aims to collect the latest 'call for reviewers' links from various top CS/ML/AI conferences/journals. It provides an opportunity for individuals in the computer/ machine learning/ artificial intelligence fields to gain review experience for applying for NIW/H1B/EB1 or enhancing their CV. The repository helps users stay updated with the latest research trends and engage with the academic community.

The Smart Connections Visualizer Plugin is a tool designed to enhance note-taking and information visualization by creating dynamic force-directed graphs that represent connections between notes or excerpts. Users can customize visualization settings, preview notes, and interact with the graph to explore relationships and insights within their notes. The plugin aims to revolutionize communication with AI and improve decision-making processes by visualizing complex information in a more intuitive and context-driven manner.