Best AI tools for< Recommend Papers >

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.

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.

Avidnote is an AI tool designed for research writing, reading, and analysis. It enables users to write or read research papers faster, analyze research data with AI templates, summarize text, find research gaps, transcribe interviews, and more. Avidnote offers AI functionalities tailored for researchers, recommended by universities, and supported by researchers worldwide. The platform provides free and paid plans with varying features and benefits to cater to different user needs.

The One-Stop Natural Language Hotel Recommender is an AI-powered tool that simplifies the process of finding the perfect hotel for your needs. By utilizing natural language processing technology, the tool can understand your preferences and requirements, and provide you with personalized hotel recommendations. It considers factors such as proximity to popular places, top-rated establishments, summarized reviews, and staying within your budget. With this tool, you can easily find the ideal accommodation for your next trip without the hassle of extensive research.

Prefixbox is an AI-powered search and discovery solution that offers a range of features to enhance user experience and boost revenue for Enterprise retailers. It provides personalized search, rich autocomplete, navigation, recommendations, insights, and analytics. Prefixbox is trusted by various industries and offers easy integration, localized language support, and market-driven development. The application helps in increasing conversion rates, average order value, and revenue through data-driven search results and relevant recommendations.

LavieTaste.AI is an AI-powered application that helps users explore and discover the best restaurants offering Singaporean and Japanese cuisine. By simply entering the desired food or place, the tool provides personalized recommendations for top dining experiences. Users can find a variety of options ranging from retro cafes to popular buffets and top steak houses. LavieTaste.AI aims to enhance the culinary journey of users by offering tailored suggestions based on their preferences and location.

AI Bookstore is a website that uses AI to help users find books that they want to read. Users can ask the AI questions about what they are looking for, and the AI will recommend books that match their criteria. The AI can also generate personalized recommendations based on a user's reading history.

Remove Objects from Photos - AI Image Eraser tool hama.app is an online tool that allows you to remove unwanted objects from your photos with just a few clicks. It uses artificial intelligence to automatically detect and remove objects, making it easy to clean up your photos and get rid of anything you don't want. With hama.app, you can remove people, objects, blemishes, and even entire backgrounds from your photos, leaving you with a clean and polished image.

Octane AI is a powerful AI tool designed for Shopify stores to create smart quizzes that drive revenue growth. It offers a no-code interface, seamless integrations with platforms like Shopify and Klaviyo, personalized product recommendations, and automated email marketing. With features like conditional logic, advanced design options, and in-depth analytics, Octane AI helps businesses engage customers, collect insights, and personalize the shopping journey. The platform is built for ecommerce marketers by ecommerce marketers, with a focus on increasing sales, boosting conversions, and fostering stronger customer relationships.

BuildShip.com is a powerful AI Assistant Builder that allows users to create AI Assistant ChatBots in just 5 minutes. The platform enables users to connect to tools and databases without the need for any code, offering full flexibility with low-code options. Users can build AI Assistants using popular models like OpenAI, Claude 3, and Azure, and can easily ship their creations as APIs, chat widgets, workflow, or schedule jobs. The platform also provides secure integration with databases, the ability to generate custom action nodes, and seamless plugin chat widgets for websites. BuildShip.com simplifies the process of building AI Assistants and empowers users to bring their ideas to life effortlessly.

Monoid is an AI tool that transforms APIs into AI Agents, enabling Large Language Models (LLMs) to act in real-time with relevant context. Users can create customizable Agents in minutes, simulate AI Agents using APIs, chat with Agents, and share Actions on the Hub. Monoid offers use-cases like Shopping Assistant, Customer Support Agent, and Workflow Automator to help businesses streamline processes and enhance customer interactions.

FINIITE AI is a retail and brand marketing solution that uses AI to help businesses grow their sales and improve customer experience. The company's flagship product is a product recommendation engine that uses AI to personalize product recommendations for each customer. FINIITE AI also offers a suite of other AI-powered solutions, including a skin check tool, a customer data insights platform, and a CRM integration. FINIITE AI's solutions are used by businesses of all sizes, from small businesses to large enterprises.

Pinecone is a vector database designed to build knowledgeable AI applications. It offers a serverless platform with high capacity and low cost, enabling users to perform low-latency vector search for various AI tasks. Pinecone is easy to start and scale, allowing users to create an account, upload vector embeddings, and retrieve relevant data quickly. The platform combines vector search with metadata filters and keyword boosting for better application performance. Pinecone is secure, reliable, and cloud-native, making it suitable for powering mission-critical AI applications.

The website, eightfold.ai, is an AI tool that offers solutions for talent acquisition and management. It leverages artificial intelligence to streamline the recruitment process, match candidates with suitable roles, and enhance workforce diversity. By utilizing advanced algorithms and machine learning, eightfold.ai aims to revolutionize how organizations discover, engage, and retain talent. The platform provides a comprehensive suite of features to optimize hiring practices and improve employee experiences.

Manifest AI is a GPT-powered AI shopping assistant designed for Shopify stores. It enhances customer experiences by providing AI-driven search, nudges, support, and quizzes for a smoother shopping journey. The application integrates with eCommerce tech stack, generates tickets on helpdesk, and offers personalized shopping experiences. Manifest AI aims to redefine ecommerce by simplifying every step of shopping with AI technology, offering intelligent and personalized shopping experiences to customers worldwide.

Shaped is a cloud-based platform that provides APIs and tools for building and deploying ranking systems. It offers a variety of features to help developers quickly and easily create and manage ranking models, including a multi-connector SQL interface, a real-time feature store, and a library of pre-built models. Shaped is designed to be scalable, cost-efficient, and easy to use, making it a great option for businesses of all sizes.

VideaHealth is a dental AI platform trusted by dentists and DSOs. It enhances diagnostics and streamlines workflows using clinical AI to identify and convert treatments across major oral conditions. The platform combines practice management system data with AI insights to elevate patient care and empower dental practices. VideaHealth offers advanced FDA-cleared detection algorithms to detect suspect diseases, provides AI-powered insights for data-driven decisions, and delivers real-time chairside assistance to dentists.

Superlinked is a compute framework for your information retrieval and feature engineering systems, focused on turning complex data into vector embeddings. Vectors power most of what you already do online - hailing a cab, finding a funny video, getting a date, scrolling through a feed or paying with a tap. And yet, building production systems powered by vectors is still too hard! Our goal is to help enterprises put vectors at the center of their data & compute infrastructure, to build smarter and more reliable software.

The AI Recruiter is an innovative AI tool designed to streamline the recruitment process by leveraging artificial intelligence technology. It offers a user-friendly platform for both job seekers and employers to connect efficiently. The tool utilizes advanced algorithms to match candidates with suitable job opportunities based on their skills and experience. With features like automated candidate screening, personalized job recommendations, and real-time notifications, the AI Recruiter simplifies the hiring process and enhances the overall recruitment experience.

VanChat is an AI shopping assistant designed to boost Shopify sales by accurately answering customer questions, understanding buyer intent, personalizing interactions, suggesting products, and ultimately increasing sales. It automates tasks like order checking and updating, offers personalized product recommendations, and proactively engages customers to drive purchases. VanChat continuously learns from store data in real-time to provide accurate responses and tailored suggestions. The platform aims to enhance user satisfaction, improve customer service, and increase revenue for online businesses.

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.

Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.

This repository is a collection of papers and resources related to recommendation systems, focusing on foundation models, transferable recommender systems, large language models, and multimodal recommender systems. It explores questions such as the necessity of ID embeddings, the shift from matching to generating paradigms, and the future of multimodal recommender systems. The papers cover various aspects of recommendation systems, including pretraining, user representation, dataset benchmarks, and evaluation methods. The repository aims to provide insights and advancements in the field of recommendation systems through literature reviews, surveys, and empirical studies.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and 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.

The AI Scientist is a comprehensive system for fully automatic scientific discovery, enabling Foundation Models to perform research independently. It aims to tackle the grand challenge of developing agents capable of conducting scientific research and discovering new knowledge. The tool generates papers on various topics using Large Language Models (LLMs) and provides a platform for exploring new research ideas. Users can create their own templates for specific areas of study and run experiments to generate papers. However, caution is advised as the codebase executes LLM-written code, which may pose risks such as the use of potentially dangerous packages and web access.

Gradient CLI is a tool designed to facilitate the end-to-end MLOps process, allowing individuals and organizations to develop, train, and deploy Deep Learning models efficiently. It supports various ML/DL frameworks and provides features such as 1-click Jupyter Notebooks, scalable model training workflows, and model deployment as API endpoints. The tool can run on different infrastructures like AWS, GCP, on-premise, and Paperspace GPUs, offering automatic versioning, distributed training, hyperparameter search, and more.

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 Awesome-LM-SSP repository is a collection of resources related to the trustworthiness of large models (LMs) across multiple dimensions, with a special focus on multi-modal LMs. It includes papers, surveys, toolkits, competitions, and leaderboards. The resources are categorized into three main dimensions: safety, security, and privacy. Within each dimension, there are several subcategories. For example, the safety dimension includes subcategories such as jailbreak, alignment, deepfake, ethics, fairness, hallucination, prompt injection, and toxicity. The security dimension includes subcategories such as adversarial examples, poisoning, and system security. The privacy dimension includes subcategories such as contamination, copyright, data reconstruction, membership inference attacks, model extraction, privacy-preserving computation, and unlearning.

LiveBench is a benchmark tool designed for Language Model Models (LLMs) with a focus on limiting contamination through monthly new questions based on recent datasets, arXiv papers, news articles, and IMDb movie synopses. It provides verifiable, objective ground-truth answers for accurate scoring without an LLM judge. The tool offers 18 diverse tasks across 6 categories and promises to release more challenging tasks over time. LiveBench is built on FastChat's llm_judge module and incorporates code from LiveCodeBench and IFEval.

Awesome-Efficient-LLM is a curated list focusing on efficient large language models. It includes topics such as knowledge distillation, network pruning, quantization, inference acceleration, efficient MOE, efficient architecture of LLM, KV cache compression, text compression, low-rank decomposition, hardware/system, tuning, and survey. The repository provides a collection of papers and projects related to improving the efficiency of large language models through various techniques like sparsity, quantization, and compression.

DB-GPT is a personal database administrator that can solve database problems by reading documents, using various tools, and writing analysis reports. It is currently undergoing an upgrade. **Features:** * **Online Demo:** * Import documents into the knowledge base * Utilize the knowledge base for well-founded Q&A and diagnosis analysis of abnormal alarms * Send feedbacks to refine the intermediate diagnosis results * Edit the diagnosis result * Browse all historical diagnosis results, used metrics, and detailed diagnosis processes * **Language Support:** * English (default) * Chinese (add "language: zh" in config.yaml) * **New Frontend:** * Knowledgebase + Chat Q&A + Diagnosis + Report Replay * **Extreme Speed Version for localized llms:** * 4-bit quantized LLM (reducing inference time by 1/3) * vllm for fast inference (qwen) * Tiny LLM * **Multi-path extraction of document knowledge:** * Vector database (ChromaDB) * RESTful Search Engine (Elasticsearch) * **Expert prompt generation using document knowledge** * **Upgrade the LLM-based diagnosis mechanism:** * Task Dispatching -> Concurrent Diagnosis -> Cross Review -> Report Generation * Synchronous Concurrency Mechanism during LLM inference * **Support monitoring and optimization tools in multiple levels:** * Monitoring metrics (Prometheus) * Flame graph in code level * Diagnosis knowledge retrieval (dbmind) * Logical query transformations (Calcite) * Index optimization algorithms (for PostgreSQL) * Physical operator hints (for PostgreSQL) * Backup and Point-in-time Recovery (Pigsty) * **Continuously updated papers and experimental reports** This project is constantly evolving with new features. Don't forget to star ⭐ and watch 👀 to stay up to date.

This paper list is about Large Language Model-enhanced Recommender System. It also contains some related works. Keywords: recommendation system, large language models

Cool-GenAI-Fashion-Papers is a curated list of resources related to GenAI-Fashion, including papers, workshops, companies, and products. It covers a wide range of topics such as fashion design synthesis, outfit recommendation, fashion knowledge extraction, trend analysis, and more. The repository provides valuable insights and resources for researchers, industry professionals, and enthusiasts interested in the intersection of AI and fashion.

A collection of papers and resources about Large Language Models (LLM) for Graph Learning (Graph). Integrating LLMs with graph learning techniques to enhance performance in graph learning tasks. Categorizes approaches based on four primary paradigms and nine secondary-level categories. Valuable for research or practice in self-supervised learning for recommendation systems.

The Alignment Handbook provides robust training recipes for continuing pretraining and aligning language models with human and AI preferences. It includes techniques such as continued pretraining, supervised fine-tuning, reward modeling, rejection sampling, and direct preference optimization (DPO). The handbook aims to fill the gap in public resources on training these models, collecting data, and measuring metrics for optimal downstream performance.

ProbSem is a repository that provides a framework to leverage large language models (LLMs) for assigning context-conditional probability distributions over queried strings. It supports OpenAI engines and HuggingFace CausalLM models, and is flexible for research applications in linguistics, cognitive science, program synthesis, and NLP. Users can define prompts, contexts, and queries to derive probability distributions over possible completions, enabling tasks like cloze completion, multiple-choice QA, semantic parsing, and code completion. The repository offers CLI and API interfaces for evaluation, with options to customize models, normalize scores, and adjust temperature for probability distributions.

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

Summarizes academic papers, explains figures and tables.

웹페이지와 해외 및 국내논문을 검색하고 박사논문쓸 정도로 전문성있게 도와줘

中文论文指导和搜索助手

根据个人研究方向，推荐专利、科普、新业务新技术、创新大赛、专利论文、研究性论文、SCI论文、课题、科技成果等的题目。

Analyzes manuscripts and recommends journals.

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