Best AI tools for< Improve Citing Skills >

Helper Systems has developed technology that restores the trust between students who want to use AI tools for research and faculty who need to ensure academic integrity. With kOS (pronounced chaos), students can easily provide proof of work using a platform that significantly simplifies and enhances the research process in ways never before possible. Add PDF files from your desktop, shared drives or the web. Annotate them if you desire. Use AI responsibly, knowing when information is generated from your research vs. the web. Instantly create a presentation of all your resources. Share and prove your work. Try other cool features that offer a unique way to find, organize, discover, archive, and present information.

Scite is an award-winning platform for discovering and evaluating scientific articles via Smart Citations. Smart Citations allow users to see how a publication has been cited by providing the context of the citation and a classification describing whether it provides supporting or contrasting evidence for the cited claim.

QOVES is a website that provides tools and advice to help people improve their looks. The website offers a variety of services, including facial analysis, hairline design, style advice, and Photoshop retouching. QOVES also has a blog with articles on a variety of topics related to beauty and aesthetics.

Zevi is an AI-powered site search and discovery platform that helps businesses improve their website search and chat experience. It offers a range of features including neural search, chat assistant, merchandising, and analytics. Zevi's AI-driven technology helps businesses understand their customers' queries and provide them with the most relevant results. It also helps businesses create a more personalized and conversational shopping experience for their customers.

FCK.School is an online platform that provides AI-powered writing tools to help students with various aspects of their academic work, including creating outlines, generating essay conclusions, crafting thesis statements, and much more. It offers a range of tools such as paraphrasing, text generation, summarizing, grammar and punctuation correction, title generation, thesis statement generation, outline generation, intro generation, paragraph generation, and conclusion generation. FCK.School aims to improve writing skills, save time and effort, and enhance the quality of written content.

Cyberday.ai is an AI-powered platform designed to help organizations improve and certify their cybersecurity. The platform offers a comprehensive set of tools and resources to guide users in implementing security tasks, creating policies, and generating compliance reports. With a focus on automation and efficiency, Cyberday.ai streamlines the process of managing information security, from risk assessment to employee training. By leveraging AI technology, Cyberday.ai aims to simplify the complex task of cybersecurity management for organizations of all sizes.

Neurala is a company that provides visual quality inspection software powered by AI. Their software is designed to help manufacturers improve their inspection process by reducing product defects, increasing inspection rates, and preventing production downtime. Neurala's software is flexible and can be easily retrofitted into existing production line infrastructure, without the need for AI experts or expensive capital expenditures. The company's software is used by a variety of manufacturers, including Sony, AITRIOS, and CB Insights.

Textbuddy is an online writing editor that uses AI to analyze and improve your writing. It highlights potential flaws in your text, such as long sentences, complex words, formatting errors, passive voice, adverbs, filler and vague words. The tool also provides synonyms, CEFR language levels, its own readability score, text statistics, and a keyword list for your text. Textbuddy's AI writing assistant can help you with grammar, spelling, and punctuation, and can even (re-)write text in plain language. You can use the AI assistant to overcome writer's block, create headlines and summaries, paraphrase text, analyze text sentiment, or just let it write for you as a copywriting AI.

DesignRoasts is a web-based tool that provides personalized AI insights to help you optimize your website or app. Simply upload a screenshot of your product and select your goal (e.g., increase conversions, improve onboarding, etc.), and DesignRoasts will generate a list of actionable feedback tailored to your specific needs. The feedback focuses on improving the user experience, visual design, copywriting, and more.

PEAR Health Labs is an AI-powered adaptive digital coaching software that offers hyperpersonalized coaching solutions to help individuals move smarter, get healthier, and live happier. The platform utilizes AI technology and physiological science to create personalized fitness experiences based on wearables and biometric feedback. PEAR Training Intelligence aims to change the landscape of preventative care by identifying health issues before they become problems. The software is cost-effective, scalable, and provides guidance on physical activity to improve overall health outcomes.

LangWatch is a monitoring and analytics tool for Generative AI (GenAI) solutions. It provides detailed evaluations of the faithfulness and relevancy of GenAI responses, coupled with user feedback insights. LangWatch is designed for both technical and non-technical users to collaborate and comment on improvements. With LangWatch, you can understand your users, detect issues, and improve your GenAI products.

Readyy is an AI-powered tool designed to help users improve their reading speed and comprehension. It offers free tools and a user-friendly dashboard to track progress. The tool leverages GPT artificial intelligence to ensure fresh tests and provides a global leaderboard for competitive practice. Readyy is beneficial for individuals of all ages, from early childhood development to adult literacy and cognitive aging. It emphasizes the importance of reading comprehension for cognitive growth, academic achievement, and critical thinking in the digital age.

Linguabot is an AI-powered language learning app that helps users improve their conversation skills. It uses natural language processing and machine learning to provide personalized feedback and exercises. Linguabot is designed to help users learn languages naturally and fluently.

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.

Lycee AI is an AI-powered learning platform that provides interactive courses, hands-on exercises, and personalized feedback to help users master Artificial Intelligence and improve their productivity.

MagickSEO is an AI-powered SEO optimization tool that helps businesses improve their website's search engine performance. With insights from millions of case studies, MagickSEO provides tailored recommendations to enhance keyword relevance, content quality, and overall SEO structure. The tool's user-friendly interface and step-by-step guidance make it easy for businesses of all sizes to optimize their websites for better visibility and organic traffic.

Sebora is an AI-powered content generation tool that helps users create engaging and SEO-friendly blog posts, articles, and other written content. It offers a range of features to simplify the content creation process, including keyword generation, article drafting, image selection, scheduling, and publishing. Sebora integrates with WordPress, making it easy for users to publish their content directly to their website. It is suitable for a variety of users, including content marketers, small business owners, and digital marketing agencies.

Recursion is a techbio company that uses artificial intelligence to accelerate drug discovery. The company's platform combines hardware, software, and data to create a more efficient and effective drug discovery process. Recursion has a broad pipeline of drug candidates in development, and it has partnered with several leading pharmaceutical companies. The company is headquartered in Salt Lake City, Utah.

Voam is a productive AI platform that helps you to automate your tasks and improve your productivity. With Voam, you can create custom AI models to automate any task, from simple data entry to complex decision-making. Voam is easy to use and requires no coding experience. You can create an AI model in minutes and start automating your tasks right away.

Gestualy is an AI application that measures and improves customer satisfaction and mood quickly and easily through gestures. It allows businesses to interact with customers or guests via gestures, make intelligent decisions, and generate valuable statistical reports using artificial intelligence. Gestualy offers touchless interaction, immediate feedback, anonymized reports on satisfaction, gender, mood, and age, as well as data protection compliance. The application is suitable for various industries, including restaurants, events, and healthcare.

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.

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.

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.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

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)

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

Awesome Responsible AI is a curated list of academic research, books, code of ethics, courses, data sets, frameworks, institutes, newsletters, principles, podcasts, reports, tools, regulations, and standards related to Responsible, Trustworthy, and Human-Centered AI. It covers various concepts such as Responsible AI, Trustworthy AI, Human-Centered AI, Responsible AI frameworks, AI Governance, and more. The repository provides a comprehensive collection of resources for individuals interested in ethical, transparent, and accountable AI development and deployment.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

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

The Everything-LLMs-And-Robotics repository is the world's largest GitHub repository focusing on the intersection of Large Language Models (LLMs) and Robotics. It provides educational resources, research papers, project demos, and Twitter threads related to LLMs, Robotics, and their combination. The repository covers topics such as reasoning, planning, manipulation, instructions and navigation, simulation frameworks, perception, and more, showcasing the latest advancements in the field.

moai is a PyTorch-based AI Model Development Kit (MDK) designed to improve data-driven model workflows, design, and understanding. It offers modularity via monads for model building blocks, reproducibility via configuration-based design, productivity via a data-driven domain modelling language (DML), extensibility via plugins, and understanding via inter-model performance and design aggregation. The tool provides specific integrated actions like play, train, evaluate, plot, diff, and reprod to support heavy data-driven workflows with analytics, knowledge extraction, and reproduction. moai relies on PyTorch, Lightning, Hydra, TorchServe, ONNX, Visdom, HiPlot, Kornia, Albumentations, and the wider open-source community for its functionalities.

LLM-as-HH is a codebase that accompanies the paper ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution. It introduces Language Hyper-Heuristics (LHHs) that leverage LLMs for heuristic generation with minimal manual intervention and open-ended heuristic spaces. Reflective Evolution (ReEvo) is presented as a searching framework that emulates the reflective design approach of human experts while surpassing human capabilities with scalable LLM inference, Internet-scale domain knowledge, and powerful evolutionary search. The tool can improve various algorithms on problems like Traveling Salesman Problem, Capacitated Vehicle Routing Problem, Orienteering Problem, Multiple Knapsack Problems, Bin Packing Problem, and Decap Placement Problem in both black-box and white-box settings.

Open-Sora-Plan is a project that aims to create a simple and scalable repo to reproduce Sora (OpenAI, but we prefer to call it "ClosedAI"). The project is still in its early stages, but the team is working hard to improve it and make it more accessible to the open-source community. The project is currently focused on training an unconditional model on a landscape dataset, but the team plans to expand the scope of the project in the future to include text2video experiments, training on video2text datasets, and controlling the model with more conditions.

SWE-agent is a tool that turns language models (e.g. GPT-4) into software engineering agents capable of fixing bugs and issues in real GitHub repositories. It achieves state-of-the-art performance on the full test set by resolving 12.29% of issues. The tool is built and maintained by researchers from Princeton University. SWE-agent provides a command line tool and a graphical web interface for developers to interact with. It introduces an Agent-Computer Interface (ACI) to facilitate browsing, viewing, editing, and executing code files within repositories. The tool includes features such as a linter for syntax checking, a specialized file viewer, and a full-directory string searching command to enhance the agent's capabilities. SWE-agent aims to improve prompt engineering and ACI design to enhance the performance of language models in software engineering tasks.

DriveLM is a multimodal AI model that enables autonomous driving by combining computer vision and natural language processing. It is designed to understand and respond to complex driving scenarios using visual and textual information. DriveLM can perform various tasks related to driving, such as object detection, lane keeping, and decision-making. It is trained on a massive dataset of images and text, which allows it to learn the relationships between visual cues and driving actions. DriveLM is a powerful tool that can help to improve the safety and efficiency of autonomous vehicles.

Cherry Data Selection project introduces a self-guided methodology for LLMs to autonomously discern and select cherry samples from open-source datasets, minimizing manual curation and cost for instruction tuning. The project focuses on selecting impactful training samples ('cherry data') to enhance LLM instruction tuning by estimating instruction-following difficulty. The method involves phases like 'Learning from Brief Experience', 'Evaluating Based on Experience', and 'Retraining from Self-Guided Experience' to improve LLM performance.

This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition: ::= | ::= | | ; Where: ; is a valid real number expressed in one of a number of given formats ; is a string of valid characters enclosed in quotes ; is one of the literal strings 'true', 'false', or 'null' (unquoted) ::=