Best AI tools for< Explore Papers >

Papers With Code is an AI tool that provides access to the latest research papers in the field of Machine Learning, along with corresponding code implementations. It offers a platform for researchers and enthusiasts to stay updated on state-of-the-art datasets, methods, and trends in the ML domain. Users can explore a wide range of topics such as language modeling, image generation, virtual try-on, and more through the collection of papers and code available on the website.

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.

OpenRead is an AI-powered research tool that offers a seamless research experience by providing access to a vast repository of over 300 million papers and trillions of web sources. It allows users to search for papers in real-time, gain valuable insights, and explore trending research topics effortlessly. With features like paper Espresso, Paper Q&A, and related Paper Graph, OpenRead aims to enhance research productivity and knowledge organization. The tool also offers the ability to disable web support for focused tasks and remembers chat history for easy reference.

mypapers.ai is an AI tool designed to assist users in managing and analyzing academic papers efficiently. The tool offers features such as exploring papers and authors, toggling between papers and authors, and tracking the journey of research. Users can also access the code on GitHub to further enhance their research capabilities.

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.

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.

Athina AI Hub is an ultimate resource for AI development teams, offering a wide range of AI development blogs, research papers, and original content. It provides valuable insights into cutting-edge technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents. Athina AI Hub aims to empower AI engineers, researchers, data scientists, and product developers by offering comprehensive resources and fostering innovation in the field of Artificial Intelligence.

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.

Replicate is an AI tool that allows users to run and fine-tune open-source models, deploy custom models at scale, and generate various types of content such as images, text, music, and speech with just one line of code. It provides a platform where users can explore and utilize thousands of production-ready AI models contributed by the community. Replicate aims to make AI accessible and practical by enabling users to push AI beyond academic papers and demos.

EssayGet is an AI tool designed to assist users in writing academic papers by providing features such as humanizing text, ensuring plagiarism-free content, generating in-text citations, and creating comprehensive outlines. The tool utilizes advanced algorithms to refine and rephrase writing, making it undetectable by top AI detectors like Turnitin, GPTZero, and Originality.ai. EssayGet aims to help students maintain the authenticity and originality of their work effortlessly, trusted by top university students for its reliable services.

Zendy is an AI-powered research library and AI assistant that empowers users to explore open access and paywalled academic literature across all disciplines. It offers tools for faster reading and citing of research papers, including AI summarization, key phrase highlighting, and organizing reading lists. With a user-friendly interface, Zendy helps users save time during literature review, making research more efficient and productive.

iLovePhD is a comprehensive research platform that serves as a one-stop solution for all research needs. It offers a wide range of services including access to journals, postdoc opportunities, scholarships, IoT security tools, job listings, datasets, and UGC-CARE journals. The platform also features ChatGPT for plagiarism detection and artificial intelligence applications. iLovePhD aims to assist researchers and academicians in publishing impactful work and staying updated with the latest trends in the academic world.

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.

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.

BioloGPT is an AI tool designed to answer biology-related questions with insights and graphs. It provides information on various topics such as maintaining a healthy gut microbiome, foods for a healthy immune system, effects of cannabis on the brain, risks of Covid-19 vaccines, and advancements in psoriasis treatment. The tool is updated daily and cites full papers to support its answers.

The website is a comprehensive platform for software development news, covering a wide range of topics such as AI, DevOps, Observability, CI/CD, Cloud Native, Data, Test Automation, Mobile, API, Performance, Security, DevSecOps, Enterprise Security, Supply Chain Security, Teams & Culture, Dev Manager, Agile, Value Stream, Productivity, and more. It provides news articles, webinars, podcasts, and white papers to keep developers informed about the latest trends and technologies in the software development industry.

Earkind is an AI-generated podcast platform that offers engaging and entertaining content by combining language models with neural expressive text-to-speech and programmatic audio editing. The platform creates full podcast episodes based on selected news and research papers, featuring lively discussions between fictional characters. Earkind aims to provide a fun and non-serious approach to Artificial Intelligence news and research, with a focus on personalized audio content.

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.

Semantic Scholar is a free, AI-powered research tool for scientific literature. It is based at the Allen Institute for AI and provides access to over 217 million papers from all fields of science. Semantic Scholar uses AI to help users discover and explore scientific literature, and to stay up-to-date on the latest research. The tool also includes a number of features to help users manage their research, such as the ability to save papers, create bibliographies, and share research with others.

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.

The Together Cookbook is a collection of code and guides designed to help developers build with open source models using Together AI. The recipes provide examples on how to chain multiple LLM calls, create agents that route tasks to specialized models, run multiple LLMs in parallel, break down tasks into parallel subtasks, build agents that iteratively improve responses, perform LoRA fine-tuning and inference, fine-tune LLMs for repetition, improve summarization capabilities, fine-tune LLMs on multi-step conversations, implement retrieval-augmented generation, conduct multimodal search and conditional image generation, visualize vector embeddings, improve search results with rerankers, implement vector search with embedding models, extract structured text from images, summarize and evaluate outputs with LLMs, generate podcasts from PDF content, and get LLMs to generate knowledge graphs.

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.

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.

This repository serves as a comprehensive hub for updates on generative AI research, interview materials, notebooks, and more. It includes monthly best GenAI papers list, interview resources, free courses, and code repositories/notebooks for developing generative AI applications. The repository is regularly updated with the latest additions to keep users informed and engaged in the field of generative AI.

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.

This repository is a curated list of research papers that explore the integration of Large Language Model (LLM) technology with tabular data. It aims to provide a comprehensive resource for researchers and practitioners interested in this emerging field. The repository includes papers on a wide range of topics, including table-to-text generation, table question answering, and tabular data classification. It also includes a section on related datasets and resources.

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.

Awesome-Graph-LLM is a curated collection of research papers exploring the intersection of graph-based techniques with Large Language Models (LLMs). The repository aims to bridge the gap between LLMs and graph structures prevalent in real-world applications by providing a comprehensive list of papers covering various aspects of graph reasoning, node classification, graph classification/regression, knowledge graphs, multimodal models, applications, and tools. It serves as a valuable resource for researchers and practitioners interested in leveraging LLMs for graph-related tasks.

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.

AudioLLMs is a curated collection of research papers focusing on developing, implementing, and evaluating language models for audio data. The repository aims to provide researchers and practitioners with a comprehensive resource to explore the latest advancements in AudioLLMs. It includes models for speech interaction, speech recognition, speech translation, audio generation, and more. Additionally, it covers methodologies like multitask audioLLMs and segment-level Q-Former, as well as evaluation benchmarks like AudioBench and AIR-Bench. Adversarial attacks such as VoiceJailbreak are also discussed.

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.

EDA-AI is a repository containing implementations of cutting-edge research papers in the field of chip design. It includes DeepPlace, PRNet, HubRouter, and PreRoutGNN models for tasks such as placement, routing, timing prediction, and global routing. Researchers and practitioners can leverage these implementations to explore advanced techniques in chip design.

This repository contains a curated list of papers focusing on the self-correction of large language models (LLMs) during inference. It covers various frameworks for self-correction, including intrinsic self-correction, self-correction with external tools, self-correction with information retrieval, and self-correction with training designed specifically for self-correction. The list includes survey papers, negative results, and frameworks utilizing reinforcement learning and OpenAI o1-like approaches. Contributions are welcome through pull requests following a specific format.

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

Awesome Large Weather Models (LWMs) is a curated collection of articles and resources related to large weather models used in AI for Earth and AI for Science. It includes information on various cutting-edge weather forecasting models, benchmark datasets, and research papers. The repository serves as a hub for researchers and enthusiasts to explore the latest advancements in weather modeling and forecasting.

The repository 'Awesome-LLM-Preference-Learning' is the official repository of a survey paper titled 'Towards a Unified View of Preference Learning for Large Language Models: A Survey'. It contains a curated list of papers related to preference learning for Large Language Models (LLMs). The repository covers various aspects of preference learning, including on-policy and off-policy methods, feedback mechanisms, reward models, algorithms, evaluation techniques, and more. The papers included in the repository explore different approaches to aligning LLMs with human preferences, improving mathematical reasoning in LLMs, enhancing code generation, and optimizing language model performance.

A guide for navigating NeurIPS 2023 all 3,586 AI papers

Summarizes academic papers, especially in medical and scientific research

Concise NeRF guide, summarizing top papers and aiding research.

I search PubMed and Google Scholar to find academic papers and articles.

深入分析无机材料及氧离子导体论文指南，主要使用中文回答。

Assistente de pesquisa em Letras com dados da CAPES

中文论文指导和搜索助手

Especialista em dados de teses e dissertações de Imunologia

Academic assistant for research on 'the Uncanny' in postmodern society and art.

Explains Arxiv papers with examples, analogies, and direct PDF links.

Explain scientific papers using the 3-pass method for efficient understanding. After uploading a paper, you can enter First pass/Second pass /Third pass / Q&A to get different level of response from SciPlore.

Know the details about the Amalgamated Intermittent Computing Systems paper

这是一个AI论文生成

I'm like a time machine, offering vivid journeys through time with accurate details.

GPT expert en astronomie, adaptable et éducatif, pour enseignement et consultation académique.

Explores attention in cognition and offers focus improvement tips.

Expands queries with tangential insights

I specialize in encouraging people to critically reflect on and explore their beliefs through Socratic questioning and neutral conversation.

Explore the infinite and your place in it.

Explore any topic with an advanced hierarchical interactive mapping with streamlined control. Begin with !start [topic].