Best AI tools for< Review Language >

Quotid is a language learning app that uses AI to generate daily lessons. The lessons are designed to be manageable and realistic, especially for those with busy schedules. The content is completely AI-generated, with all of the good, and some of the bad. The diversity of speech and topics makes it a very valuable language learning partner, best used as an addition to other efforts. Apart from the daily lesson, you can sign in, track your lesson history and revisit the vocabulary you covered so far.

Spellbook is an AI contract drafting and review tool designed to help legal professionals draft and review contracts efficiently. It uses AI technology to suggest terms, generate redlines, draft new clauses, detect aggressive terms, and provide negotiation suggestions. Spellbook is trusted by over 2,500 law firms and in-house legal teams, offering a comprehensive solution for legal document creation and review.

The Art Review Generator is a natural language processing tool and text generator that analyzes and generates language used to describe art and culture. It utilizes a vast amount of training data from 57 years of art reviews to create medium-length sentences. While not classified as artificial intelligence, it employs deep matrices of probability to generate text based on the input prompt. The tool focuses on modern art reviews, capturing the distinctive language of human expression, including intent, emotion, technique, and impact. Despite potential biases and glitches, it offers insights into the evolution of language in art critiques over the years.

PaperClip is an AI tool designed to help users keep track of their daily AI papers review. It allows users to memorize details from papers in machine learning, computer vision, and natural language processing. The tool offers an extension that enables users to find back important findings from AI research papers, ML blog posts, and news. PaperClip's AI runs locally, ensuring data privacy by not sending any information to external servers. Users can save and index their bits locally, with offline support for searching even without an internet connection. Additionally, users can clean their data anytime, reset saved bits, and delete all data with ease.

Beebzi.AI is an all-in-one AI content creation platform that offers a wide array of tools for generating various types of content such as articles, blogs, emails, images, voiceovers, and more. The platform utilizes advanced AI technology and behavioral science to empower businesses and individuals in their marketing and sales endeavors. With features like AI Article Wizard, AI Room Designer, AI Landing Page Generator, and AI Code Generation, Beebzi.AI revolutionizes content creation by providing customizable templates, multiple language support, and real-time data insights. The platform also offers various subscription plans tailored for individual entrepreneurs, teams, and businesses, with flexible pricing models based on word count allocations. Beebzi.AI aims to streamline content creation processes, enhance productivity, and drive organic traffic through SEO-optimized content.

Review Bomb Me is an AI-powered software that helps businesses convert negative reviews into constructive and positive ones. It uses AI to summarize reviews and add them to a dashboard, where businesses can monitor how their Review Bomb is going. Review Bomb Me also provides businesses with a personal user analytics dashboard, so they can see who is engaging with their content and where they are coming from.

MIT Technology Review is a world-renowned, independent media company whose insight, analysis, reviews, interviews and live events explain the newest technologies and their commercial, social and political impact.

PullRequest is an AI-powered code review as a service platform that offers on-demand code review from expert engineers enhanced by AI. It supports all languages and frameworks, helping development teams of any size ship better, more secure code faster through AI-assisted code reviews. PullRequest integrates with popular version control platforms like GitHub, GitLab, Bitbucket, and Azure DevOps, providing valuable knowledge sharing with senior engineers to improve code quality and security. The platform ensures code safety and security by adhering to best practices, strict procedures, and employing reviewers based in the US, the UK, or Canada.

Metabob is an AI-powered code review tool that helps developers detect, explain, and fix coding problems. It utilizes proprietary graph neural networks to detect problems and LLMs to explain and resolve them, combining the best of both worlds. Metabob's AI is trained on millions of bug fixes performed by experienced developers, enabling it to detect complex problems that span across codebases and automatically generate fixes for them. It integrates with popular code hosting platforms such as GitHub, Bitbucket, Gitlab, and VS Code, and supports various programming languages including Python, Javascript, Typescript, Java, C++, and C.

NewWord is an AI-powered language learning tool designed to help users memorize and expand their vocabulary efficiently. It offers innovative features such as personalized word management solutions, AI-powered insights, and a unique traceability system. The application aims to make language learning more convenient and enjoyable by providing diversified review strategies and daily reminders. NewWord is suitable for individuals looking to enhance their linguistic skills through practical exercises and scenario-based learning modules.

Diligen is a machine learning powered contract analysis tool that helps teams streamline their contract review process. It can identify key provisions, generate contract summaries, and help teams manage review with machine learning powered analysis. Diligen is used by law firms, legal service providers, and corporations around the world to make high quality contract review faster, more efficient, and more cost effective.

Reply with AI is a free tool that helps businesses write the perfect review reply in seconds. It uses artificial intelligence to generate personalized and professional replies that can help businesses save time and improve their customer service. Reply with AI integrates with Google Seller Ratings, Salesforce, and other popular platforms, making it easy for businesses to manage their online reputation. With Reply with AI, businesses can quickly and easily respond to reviews, build trust with customers, and improve their overall online presence.

editoReview is a consulting platform and marketplace that helps academic editors and marketing agents to review the AI intelligence at the interface of research articles and service plugins API by consulting with authors and developers. It allows users to start a new review using an AI chat transcript or from a template document, cite the reference paper or app to schedule a consultation meeting with the author or developer, and pay the optional consultation and publish the review transcripts with shareable links.

Effy AI is a free performance management software for teams. It is AI-powered and backed by Run your first 360 review in 60 sec. Fast, and stress-free 360 feedback and performance review software build for teams. With Effy AI, you can collect reviews from different sources such as self, peer, manager, and subordinate evaluations. The platform goes even further by allowing employees to suggest particular peers and seek approval from their manager, giving them a voice in their reviews. Effy AI uses cutting-edge artificial intelligence to carefully process reviewers' answers and generate comprehensive reports for each employee based on the review responses.

Endorsed is an AI-powered recruiting tool that helps companies review job applications more efficiently and effectively. It integrates with your existing applicant tracking system (ATS) to provide you with a co-pilot that can help you screen and rank candidates, identify top talent, and make better hiring decisions. Endorsed uses machine learning to analyze candidate resumes and applications, and then ranks them based on your specific criteria. This helps you to identify the most qualified candidates quickly and easily, so you can spend less time reviewing applications and more time interviewing the best candidates.

AnkiDecks is an online tool that helps users generate flashcards from files or text using AI. It supports various file formats, including PDFs, Word documents, PowerPoint presentations, and text files. The generated flashcards can be used for studying purposes, particularly for language learning. AnkiDecks also offers features such as cloze (fill-in-the-blank) flashcards and text-to-speech functionality for language flashcards. Users can import the generated flashcards into the popular flashcard software Anki for further review and practice.

VideoDubber is an AI-powered video translation and voice cloning tool that allows users to translate videos into over 150 languages with just one click. It also offers features such as voice cloning, text-to-speech, and subtitling. VideoDubber is designed to help businesses and content creators reach a global audience by making their videos accessible to viewers who speak different languages.

VideoDubber is an AI-powered video translation and voice cloning tool that allows users to translate videos into over 150 languages with just one click. It also offers features such as voice cloning, text-to-speech, and subtitling. VideoDubber is a valuable tool for businesses and content creators who want to reach a global audience with their videos.

Breadcrumb.ai is an AI data analytics platform that enables users to combine, analyze, and chat with their files using AI data analytic agents. The platform is designed to be intuitive, eliminating the need for coding or data expertise. Breadcrumb's AI agents integrate and clean data, allowing users to ask questions in plain language and generate dashboards effortlessly. The tool provides a visual analytic canvas for exploring data, facilitating communication and collaboration across teams in real-time. With Breadcrumb, users can streamline operations, accelerate sales, and drive marketing decisions with evidence-based insights.

DrugCard is an AI-enabled Data Intelligence platform designed to streamline drug safety routines for pharmacovigilance processes. It offers solutions for local literature screening, catering to CROs, MAHs, and freelancers in the pharmaceutical industry. With support for multiple languages and regions, DrugCard ensures continuous, transparent, and scalable drug safety processes, saving time and improving efficiency. The platform leverages AI technology to enhance pharmacovigilance practices, providing accurate and holistic screening of medical journals to meet regulatory requirements.

Awesome-Story-Generation is a repository that curates a comprehensive list of papers related to Story Generation and Storytelling, focusing on the era of Large Language Models (LLMs). The repository includes papers on various topics such as Literature Review, Large Language Model, Plot Development, Better Storytelling, Story Character, Writing Style, Story Planning, Controllable Story, Reasonable Story, and Benchmark. It aims to provide a chronological collection of influential papers in the field, with a focus on citation counts for LLMs-era papers and some earlier influential papers. The repository also encourages contributions and feedback from the community to improve the collection.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

AI-resources is a repository containing links to various resources for learning Artificial Intelligence. It includes video lectures, courses, tutorials, and open-source libraries related to deep learning, reinforcement learning, machine learning, and more. The repository categorizes resources for beginners, average users, and advanced users/researchers, providing a comprehensive collection of materials to enhance knowledge and skills in AI.

The repository 'Awesome-LLM4Cybersecurity' provides a comprehensive overview of the applications of Large Language Models (LLMs) in cybersecurity. It includes a systematic literature review covering topics such as constructing cybersecurity-oriented domain LLMs, potential applications of LLMs in cybersecurity, and research directions in the field. The repository analyzes various benchmarks, datasets, and applications of LLMs in cybersecurity tasks like threat intelligence, fuzzing, vulnerabilities detection, insecure code generation, program repair, anomaly detection, and LLM-assisted attacks.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

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.

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.

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.

Awesome LLM for APR is a repository dedicated to exploring the capabilities of Large Language Models (LLMs) in Automated Program Repair (APR). It provides a comprehensive collection of research papers, tools, and resources related to using LLMs for various scenarios such as repairing semantic bugs, security vulnerabilities, syntax errors, programming problems, static warnings, self-debugging, type errors, web UI tests, smart contracts, hardware bugs, performance bugs, API misuses, crash bugs, test case repairs, formal proofs, GitHub issues, code reviews, motion planners, human studies, and patch correctness assessments. The repository serves as a valuable reference for researchers and practitioners interested in leveraging LLMs for automated program repair.

Code Review GPT uses Large Language Models to review code in your CI/CD pipeline. It helps streamline the code review process by providing feedback on code that may have issues or areas for improvement. It should pick up on common issues such as exposed secrets, slow or inefficient code, and unreadable code. It can also be run locally in your command line to review staged files. Code Review GPT is in alpha and should be used for fun only. It may provide useful feedback but please check any suggestions thoroughly.

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.

Efficient Multimodal Large Language Models: A Survey provides a comprehensive review of efficient and lightweight Multimodal Large Language Models (MLLMs), focusing on model size reduction and cost efficiency for edge computing scenarios. The survey covers the timeline of efficient MLLMs, research on efficient structures and strategies, and applications. It discusses current limitations and future directions in efficient MLLM research.

Efficient Multimodal Large Language Models: A Survey provides a comprehensive review of efficient and lightweight Multimodal Large Language Models (MLLMs), focusing on model size reduction and cost efficiency for edge computing scenarios. The survey covers the timeline of efficient MLLMs, research on efficient structures and strategies, and their applications, while also discussing current limitations and future directions.

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.

xef.ai is a one-stop library designed to bring the power of modern AI to applications and services. It offers integration with Large Language Models (LLM), image generation, and other AI services. The library is packaged in two layers: core libraries for basic AI services integration and integrations with other libraries. xef.ai aims to simplify the transition to modern AI for developers by providing an idiomatic interface, currently supporting Kotlin. Inspired by LangChain and Hugging Face, xef.ai may transmit source code and user input data to third-party services, so users should review privacy policies and take precautions. Libraries are available in Maven Central under the `com.xebia` group, with `xef-core` as the core library. Developers can add these libraries to their projects and explore examples to understand usage.

A DEI language reviewer, ensuring inclusivity and accessibility in written content.

Region-specific Tesla info in multiple languages for beginners.

Expert in Language Quality Assessment for translations.

Creative review starts now

code security expert to do code review

The KQL Query Helper GPT is tailored specifically for assisting users with Kusto Query Language (KQL) queries. It leverages extensive knowledge from Azure Data Explorer documentation to aid users in understanding, reviewing, and creating new KQL queries based on their prompts.

A gastroenterology board review aid

for relevant literature review and recent

Translates medical reports into simple language, not for diagnostics.

Assists in resume review and interview question creation based on job description.

Personal legal advisor, fluent in German and Chinese, for contract review and explanation

Improved ChatGPT with Response Review and Persistent Contexts

Expert in medical article analysis and review writing.

a robot scholar reviewing social science research

Expert in IELTS Test Prep, offering tailored advice, resources, and joyful encouragement.

Creates educational flashcards and integrates with Anki.

Convert knowledge into flashcard format

specialized GPT designed to assist with drafting and understanding legal clauses. It's equipped with a deep understanding of legal terminology and the structure of legal documents.

Convert simple documents and notes into supported legal terminology. Copyright (C) 2024, Sourceduty - All Rights Reserved.

A scholarly guide to Whitehead's early work in 'The Concept of Nature'.