Best AI tools for< Format Papers >

PaperGen is an AI-powered platform designed to assist users in creating visually impressive papers. It offers features such as AI knowledge curation, AI outline generation, and AI paper generation and formatting. With real-time updates and a user-friendly interface, PaperGen aims to streamline the writing process for various types of documents, including essays, research papers, blog posts, and literature reviews. Trusted by universities and businesses worldwide, PaperGen helps users effectively tell their stories and amplify their voices through storytelling.

Bibit AI is a real estate marketing AI designed to enhance the efficiency and effectiveness of real estate marketing and sales. It can help create listings, descriptions, and property content, and offers a host of other features. Bibit AI is the world's first AI for Real Estate. We are transforming the real estate industry by boosting efficiency and simplifying tasks like listing creation and content generation.

Edde.ai is an AI-powered academic writing assistant designed to streamline the academic journey of students and researchers. It offers a range of tools such as real-time suggestions, grammar checks, and stylistic improvements to enhance writing quality. Additionally, Edde.ai provides features like title and outline generation, research helper, citation manager, subject guides, and question solver to simplify the research process. With transparent pricing and a user-friendly interface, Edde.ai aims to empower users in creating high-quality academic content.

PicNotes is a web-based image-to-text converter that can convert messy images into summaries, text, or explanations. It supports handwritten papers, medical reports, and other types of images. The tool is easy to use: simply upload an image and choose the desired output format. PicNotes will then process the image and return the results within seconds.

The Computer Vision Foundation (CVF) is a non-profit organization dedicated to advancing the field of computer vision. CVF organizes several conferences and workshops each year, including the International Conference on Computer Vision (ICCV), the Conference on Computer Vision and Pattern Recognition (CVPR), and the Winter Conference on Applications of Computer Vision (WACV). CVF also publishes the International Journal of Computer Vision (IJCV) and the Computer Vision and Image Understanding (CVIU) journal. The CVF Open Access website provides access to the full text of all CVF-sponsored conference papers. These papers are available for free download in PDF format. The CVF Open Access website also includes links to the arXiv versions of the papers, where available.

Deep Cognition offers PaperEntry AI, an Intelligent Document Processing solution powered by generative AI. It automates data entry tasks with high accuracy, scalability, and configurability, handling complex documents of any type or format. The application is trusted by leading global organizations for customs clearance automation and government document processing, delivering significant time and cost savings. With industry-specific features and a proven track record, Deep Cognition provides a state-of-the-art solution for businesses seeking efficient data extraction and automation.

Unifire.ai is an AI-powered content repurposing tool that allows users to create content 10 times faster by transforming audio, text, and video content into various formats such as Tweets, LinkedIn posts, newsletters, and blog posts. The tool is trained on the user's tone and style, providing unique and personalized content. Unifire automates the content generation process, from transcription to final content creation, enabling users to scale their existing content without starting from scratch. It offers collaborative editing features, content templates, and a credit-based pricing system for cost-effective usage.

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.

Scholarcy is an AI-powered tool designed to help students and researchers summarize, analyze, and organize their research efficiently. It converts long and complex texts into interactive summary flashcards, highlights key information, and guides users to important sections of text. Scholarcy also offers features to enhance summaries, critically evaluate texts, organize knowledge, and synthesize insights. With compatibility across various file formats and sources, Scholarcy aims to revolutionize research workflows and save users valuable time.

Parafrasear.ai is an advanced AI-powered paraphrasing tool that helps users rewrite existing text, ideas, and information using different words. It offers various modes of rewriting, such as general, anti-plagiarism, fluency, academic, blog, and formal, catering to different user needs. The tool ensures contextual accuracy in paraphrased content, making it ideal for writers, SEO executives, students, marketers, and researchers. With features like free usage, compatibility across devices, plagiarism-free rewriting, customization options, and user-friendly interface, Parafrasear.ai stands out as a reliable platform for text paraphrasing in Spanish.

Afforai is a powerful AI research assistant and chatbot that serves as an AI-powered reference manager for researchers. It helps manage, annotate, cite papers, and conduct literature reviews with AI reliably. With features like managing research papers, annotating and highlighting notes, managing citations and metadata, collaborating on notes, and supporting various document formats, Afforai streamlines academic workflows and enhances research productivity. Trusted by over 50,000 researchers worldwide, Afforai offers advanced AI capabilities, including GPT-4 and Claude 3.5 Sonnet, along with secure data handling and seamless integrations.

PrepAI is an advanced AI-powered test generator platform designed to streamline the test creation, conducting, and grading process for educators, students, and ed-tech companies worldwide. With features like AI-generated quizzes, auto-grading system, and multiple question formats, PrepAI offers a one-stop assessment solution for hassle-free examinations. The platform aims to enhance critical thinking skills, save time, and resources, and provide a seamless user experience for creating and sharing online tests and quizzes.

AnySolve is an AI-powered platform that offers a wide range of tools to automate tasks and save time. Users can access tools like AI Chat, Write Like Anyone, Wikipedia Article Creation, Create Credit Contract, Answer Exam Question, and more. AnySolve allows users to create and share their own AI tools, discover existing tools, and integrate various AI capabilities into their workflows. The platform provides a user-friendly interface and supports multiple output formats, making it a versatile solution for professionals across different industries.

ASSIST is an AI-driven document management software designed to streamline financial paperwork processing and data entry tasks. The application offers features such as SmartDoc Entry for extracting information from invoices and receipts, Polyglot Processing for multilingual support, One-Tap Integration with accounting platforms, ExportEase for data export in CSV format, and AutoFlow Revolution for automated workflows. ASSIST aims to simplify document management, enhance efficiency, and drive digital transformation in businesses by leveraging AI technology.

The Visualizer is an AI-powered tool designed to map out and summarize various types of content such as papers, YouTube videos, documents, podcasts, websites, lectures, articles, and PDFs. It helps users cut down reading time and absorb knowledge faster by providing visual summaries. The tool is trusted by over 3000 educators and learners and is known for its superb performance on different devices. The Visualizer uses AI-generated mind maps to simplify complex topics into visual formats, making it easier to understand and remember detailed concepts. It also reduces mental strain, allowing users to focus better on creative solutions and everyday problem-solving.

LedgerBox is an AI tool that specializes in converting bank statements into digital formats. It simplifies the process of managing financial data by automatically extracting and organizing information from bank statements. With LedgerBox, users can easily convert paper-based bank statements into digital files, enabling quick and efficient financial analysis and reporting. The tool is designed to save time and reduce errors associated with manual data entry, making it a valuable asset for individuals and businesses looking to streamline their financial processes.

包阅AI is an intelligent AI reading assistant that covers various scenarios such as paper reading, legal analysis, scientific research, marketing, education, brand analysis, and business understanding. It supports multiple document formats like PDF, Word, PPT, EPUB, Mobi, TXT, and Markdown. The tool offers features like document interpretation, web page summarization, contract review, resume analysis, and financial document analysis. With the ability to analyze over 50,000 documents and assist more than 100,000 knowledge workers efficiently, it aims to enhance work and study productivity through AI-powered assistance.

Format Magic is a one-click formatting platform powered by AI that transforms plain text into beautifully formatted documents within seconds. Users can select a template, paste their text, and let the AI automatically apply headings and styles to create professional resumes or documents effortlessly. The platform offers easy-to-use tools for quick and efficient formatting, making it a valuable resource for individuals looking to enhance the visual appeal of their written content.

Resumy is an AI-powered resume builder that uses OpenAI's GPT-4 natural language processing model to generate polished and effective resumes. It analyzes a user's work experience, skills, and achievements to create a professional-looking resume in minutes. Resumy also offers proven templates and personalized help from resume writing experts.

Letterfy is an AI-powered cover letter generator that helps job seekers create high-quality cover letters quickly and easily. With Letterfy, you can generate a professional cover letter in minutes, tailored to the specific job you're applying for. Letterfy's AI technology analyzes your resume and LinkedIn profile to identify your skills and experience, and then generates a cover letter that highlights your most relevant qualifications. You can also customize your cover letter with your own personal touch, and download it in PDF format.

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.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

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.

This repository contains a collection of research papers related to watermarking techniques for text and images, specifically focusing on large language models (LLMs). The papers cover various aspects of watermarking LLM-generated content, including robustness, statistical understanding, topic-based watermarks, quality-detection trade-offs, dual watermarks, watermark collision, and more. Researchers have explored different methods and frameworks for watermarking LLMs to protect intellectual property, detect machine-generated text, improve generation quality, and evaluate watermarking techniques. The repository serves as a valuable resource for those interested in the field of watermarking for LLMs.

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.

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 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.

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.

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.

**Curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.** **Description in less than 400 words, no line breaks and quotation marks.** Large Language Models (LLMs) have revolutionized the NLP landscape, showing improved performance and sample efficiency over smaller models. However, increasing model size alone has not proved sufficient for high performance on challenging reasoning tasks, such as solving arithmetic or commonsense problems. This curated collection of papers and resources presents the latest advancements in unlocking the reasoning abilities of LLMs and Multimodal LLMs (MLLMs). It covers various techniques, benchmarks, and applications, providing a comprehensive overview of the field. **5 jobs suitable for this tool, in lowercase letters.** - content writer - researcher - data analyst - software engineer - product manager **Keywords of the tool, in lowercase letters.** - llm - reasoning - multimodal - chain-of-thought - prompt engineering **5 specific tasks user can use this tool to do, in less than 3 words, Verb + noun form, in daily spoken language.** - write a story - answer a question - translate a language - generate code - summarize a document

Prompt4ReasoningPapers is a repository dedicated to reasoning with language model prompting. It provides a comprehensive survey of cutting-edge research on reasoning abilities with language models. The repository includes papers, methods, analysis, resources, and tools related to reasoning tasks. It aims to support various real-world applications such as medical diagnosis, negotiation, etc.

Deep Lake is a Database for AI powered by a storage format optimized for deep-learning applications. Deep Lake can be used for: 1. Storing data and vectors while building LLM applications 2. Managing datasets while training deep learning models Deep Lake simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in your own cloud and in one place. Deep Lake is used by Intel, Bayer Radiology, Matterport, ZERO Systems, Red Cross, Yale, & Oxford.

Awesome-LLM-Inference: A curated list of 📙Awesome LLM Inference Papers with Codes, check 📖Contents for more details. This repo is still updated frequently ~ 👨‍💻‍ Welcome to star ⭐️ or submit a PR to this repo!

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.

LLM4EDA is a repository dedicated to showcasing the emerging progress in utilizing Large Language Models for Electronic Design Automation. The repository includes resources, papers, and tools that leverage LLMs to solve problems in EDA. It covers a wide range of applications such as knowledge acquisition, code generation, code analysis, verification, and large circuit models. The goal is to provide a comprehensive understanding of how LLMs can revolutionize the EDA industry by offering innovative solutions and new interaction paradigms.

A curated list of open-ended learning AI resources focusing on algorithms that invent new and complex tasks endlessly, inspired by human advancements. The repository includes papers, safety considerations, surveys, perspectives, and blog posts related to open-ended AI research.

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.

Awesome-LLM-Interpretability is a curated list of materials related to LLM (Large Language Models) interpretability, covering tutorials, code libraries, surveys, videos, papers, and blogs. It includes resources on transformer mechanistic interpretability, visualization, interventions, probing, fine-tuning, feature representation, learning dynamics, knowledge editing, hallucination detection, and redundancy analysis. The repository aims to provide a comprehensive overview of tools, techniques, and methods for understanding and interpreting the inner workings of large language models.

Editing and polishing your research papers professionally in an easy way!

Expert in all academic in-text citation styles.

The Writing Metier Footnote Assistant is a specialized GPT model designed to help students efficiently create, format, and verify footnotes for their academic papers.

A university-level paper grader and advisor, specialized in APA format

Generates APA papers with detailed reference lists.

以代码框形式输出英文论文摘录的格式化，自动生成中文小标题。

是一个可以帮助你撰写核心期刊专利论文的功能。它可以根据你的专利信息、研究背景、创新点、实施效果等信息，为你生成一份符合格式要求和技术要求的专利论文草稿，包括标题、摘要、关键词、引言、专利介绍、实施效果、结论和参考文献等。它还可以提供一些参考文献和范文，帮助你完善和优化你的专利论文。

是一个可以帮助你撰写核心期刊研究性论文的功能。可以根据你的研究问题、研究目的、研究方法、研究结果和研究结论等信息，为你生成一份符合格式要求和内容要求的研究性论文草稿，包括标题、摘要、关键词、引言、文献综述、研究设计、数据分析、讨论和参考文献等。还可以提供一些参考文献和范文，帮助你完善和优化你的研究性论文。

Expert in academic economic article writing and Latex formatting on Overleaf.

Scientific English-Chinese translator with markdown table output.

Converts book and news URLs to BibTeX

Ensuring highest excellence in academic writing

Writing assistant for architecture dissertations

Spanish academic, Christian, APA, focused on direct quotes.

Desenvolver um assistente baseado em GPTs para auxiliar na criação de trabalhos escolares (ABNT)

学术型润色纠错机器人ZT

Expert in BVM Workshop paper submission guidelines.

LaTeX paper writing assistant and PDF formatter

I convert and turn formal text to informal style instantly. Simply put your formal text below and click Enter! Perfect for sentences, paragraphs, and daily messages.

Formal and academic Mandarin writing assistant with an IEEE focus.