Best AI tools for< Improve Research Quality >

Roundtable is an AI-assisted data cleaning tool that helps improve market research data quality by efficiently analyzing and cleaning survey data. It offers an easy-to-integrate API for cleaning open-ended survey responses, saving users up to 70% of their time. The tool is trusted by leaders in over 25 global markets and provides real-time behavioral tracking, multilingual functionality, and dynamic clustering to enhance data quality and accuracy.

Elsevier is an information analytics business that supports researchers and healthcare professionals in advancing science and improving healthcare outcomes. They provide high-quality data and analytics to help researchers, librarians, and research leaders address challenges at every stage of the research journey. Elsevier offers researcher tools, research management solutions, and evaluation services to enhance productivity and research impact.

Cercle is an AI platform that advances healthcare for women by transforming healthcare data into real-time, high-quality insights. The platform caters to women's healthcare providers, payors, and pharma companies, helping them run more efficient businesses and provide personalized care. Cercle's Biomedical Graph unlocks insights at unprecedented speed and accuracy, optimizing patient care and improving outcomes in areas such as assisted reproduction and fertility processes.

Subscribr is an AI tool designed exclusively for YouTube scriptwriting, aiming to revolutionize the script creation process by providing fast ideation, high-quality research, scriptwriting on easy mode, instant feedback, and the ability to remix proven viral videos. Founded by Gil Hildebrand, Subscribr addresses the common challenges faced by content creators on YouTube, offering a solution that streamlines the scriptwriting workflow and enhances the overall quality of video content.

Branded Research, acquired by Dynata, provides access to AI-verified audience insights. It offers a range of research methods, including surveys, webcam studies, and emotional AI. With its advanced algorithms and extensive profiling, Branded helps businesses connect with their target audience and gain valuable insights to drive innovation. The company serves various industries, including tech, consumer goods, healthcare, and research agencies.

LLM Quality Beefer-Upper is an AI tool designed to enhance the quality and productivity of LLM responses by automating critique, reflection, and improvement. Users can generate multi-agent prompt drafts, choose from different quality levels, and upload knowledge text for processing. The application aims to maximize output quality by utilizing the best available LLM models in the market.

Genei is an AI-powered summarization and research tool that helps users with qualitative research, content production, academic writing, and professional writing. It enables users to research faster by automatically summarizing background reading and producing blogs, articles, and reports efficiently. Genei offers features such as summarization, keyword extraction, document management, annotation capabilities, and citation management. Trusted by thought leaders and experts, Genei enhances productivity, saves time, and improves the quality and efficiency of research and writing tasks.

Looppanel is a user research analysis and repository tool that uses AI to help researchers save time and improve the quality of their work. It offers a range of features, including automated transcription, AI note-taking, video snipping, and advanced search capabilities. Looppanel is designed to make it easy for researchers to capture, organize, and analyze their research data, so they can focus on what matters most: uncovering insights and making better decisions.

SEO.ai is an AI-powered content writing and optimization platform designed to help businesses improve their search engine rankings and drive more organic traffic to their websites. The platform offers a range of features, including AI-generated content, keyword research, and SEO optimization tools, all designed to make it easier for businesses to create high-quality, search engine-friendly content.

ProdMoh AI is an AI tool designed to assist Product Managers and Founders in transforming product development processes. It leverages AI-powered insights and tools to streamline workflow, prioritize effectively, and drive innovation. With ProdMoh AI, users can create, strategize, and validate product ideas in minutes, organize their vision effortlessly, understand users on a deeper level, and conduct user research in a reimagined way.

Siuuu.ai is an AI writing tool designed to be your most powerful copilot in the writing process. It utilizes advanced artificial intelligence algorithms to assist users in generating high-quality written content efficiently. With Siuuu.ai, users can enhance their writing productivity, creativity, and accuracy. The tool provides intelligent suggestions, grammar corrections, and content optimization features to streamline the writing workflow. Whether you are a professional writer, student, or business owner, Siuuu.ai can help you elevate your writing skills and produce compelling content with ease.

Texta is an AI-powered blog writing tool that helps users create high-quality, SEO-optimized content. It offers a range of features, including automated blog generation and posting, smart linking, keyword research, and seamless integration with popular website builders. Texta is designed to help users streamline their content creation process, boost their SEO rankings, and enhance reader engagement.

Stylus is an AI-powered essay writing tool designed to assist students in creating academic papers. It offers features such as AI-driven editor, paper generator, and personal statement writer. Stylus provides comprehensive and well-structured writing, uses reliable sources, and ensures stylistic accuracy. The tool is multilingual, works on mobile devices, and guarantees original content without plagiarism. Users can benefit from the AI's ability to understand personal writing style and voice, making the writing process efficient and insightful.

My Free Essay Generator is an AI-powered tool that simplifies the essay writing process by generating well-structured, high-quality essays on various topics. Users can input their requirements and let the AI create personalized content for different essay types and academic levels. The tool offers customizable features to meet specific length and citation format needs, ensuring error-free and engaging writing. With benefits like time-saving, consistency, and creativity enhancement, this AI application revolutionizes essay writing for students and professionals alike.

QuillWord is an AI-powered text editor designed to enhance academic and research writing. It offers a range of AI-powered tools, including an email writer, text summarizer, outline generator, essay rewriter, essay extender, essay shortener, essay introduction generator, essay conclusion generator, essay topic generator, research title generator, abstract generator, essay checker, and AI-powered autocompletion. QuillWord also provides citation support in various styles, a reference library, and an AI assistant called Copilot. It is suitable for students, teachers, researchers, and writers who want to improve their writing efficiency and quality.

Tribe AI is a modern consultancy specializing in AI, data, and machine learning, helping organizations leverage artificial intelligence. The platform offers bespoke AI solutions, advisory services, and GenAI acceleration to unlock the potential of cutting-edge technology. Tribe AI connects top AI talent with companies across various industries, such as healthcare, venture capital, insurance, private equity, and technology, to optimize operations and drive innovation. The platform also features a network of experienced AI researchers, data scientists, ML engineers, and AI fairness experts, ensuring high-quality and secure AI solutions for clients.

Innhold.ai is an AI-powered writing assistant designed to enhance your writing experience. It offers advanced features such as grammar checking, sentence restructuring, and vocabulary enhancement to help you create high-quality content. With its intuitive interface, users can easily improve their writing skills and productivity. Whether you are a student, professional writer, or content creator, Innhold.ai can assist you in crafting engaging and error-free text.

AHelp is the ultimate hub of educational and AI writing tools designed to assist students in improving their writing skills, enhancing efficiency, and achieving academic success. The platform offers a variety of powerful AI tools and applications such as Paraphraser, Grammar Checker, Plagiarism Checker, AI Detector, AI Essay Writer, Summarizer, and Citation Generator. AHelp is a one-stop solution for better writing, providing confidentiality, privacy, and a money-back guarantee. With a mission to empower students from top universities, AHelp ensures 100% compliance with academic standards, a significant improvement in writing quality, and a faster writing and research process.

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.

Prompt Genie is a powerful tool that helps you generate high-quality prompts for ChatGPT. With Prompt Genie, you can easily create prompts for a wide variety of tasks, including crafting video hooks, improving video scripts, creating ideal customer profiles, finding value propositions, creating brand identities, marketing plans, copywriting using the PAS Framework, creating lesson outlines, and writing argumentative essays. Prompt Genie is easy to use and affordable, and it can help you save time and improve the quality of your work.

This repository is a collection of research lectures and experience sharing posts from frontline researchers in the field of AI. It aims to help individuals upgrade their research skills and knowledge through insightful talks and experiences shared by experts. The content covers various topics such as evaluating research papers, choosing research directions, research methodologies, and tips for writing high-quality scientific papers. The repository also includes discussions on academic career paths, research ethics, and the emotional aspects of research work. Overall, it serves as a valuable resource for individuals interested in advancing their research capabilities in the field of AI.

This repository aims to promote global equality for individuals pursuing a PhD in NLP by providing resources and information on various aspects of the academic journey. It covers topics such as applying for a PhD, getting research opportunities, preparing for the job market, and succeeding in academia. The repository is actively updated and includes contributions from experts in the field.

This repository is a curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their variants. It includes tutorials, papers, tools, frameworks, and best practices to aid researchers, data scientists, and machine learning practitioners in adapting pre-trained models to specific tasks and domains. The resources cover a wide range of topics related to fine-tuning LLMs, providing valuable insights and guidelines to streamline the process and enhance model performance.

GenAI Agents is a comprehensive repository for developing and implementing Generative AI (GenAI) agents, ranging from simple conversational bots to complex multi-agent systems. It serves as a valuable resource for learning, building, and sharing GenAI agents, offering tutorials, implementations, and a platform for showcasing innovative agent creations. The repository covers a wide range of agent architectures and applications, providing step-by-step tutorials, ready-to-use implementations, and regular updates on advancements in GenAI technology.

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.

This repository provides a comprehensive collection of AI tools and resources to enhance literature reviews. It includes a curated list of AI tools for various tasks, such as identifying research gaps, discovering relevant papers, visualizing paper content, and summarizing text. Additionally, the repository offers materials on generative AI, effective prompts, copywriting, image creation, and showcases of AI capabilities. By leveraging these tools and resources, researchers can streamline their literature review process, gain deeper insights from scholarly literature, and improve the quality of their research outputs.

DevQualityEval is an evaluation benchmark and framework designed to compare and improve the quality of code generation of Language Model Models (LLMs). It provides developers with a standardized benchmark to enhance real-world usage in software development and offers users metrics and comparisons to assess the usefulness of LLMs for their tasks. The tool evaluates LLMs' performance in solving software development tasks and measures the quality of their results through a point-based system. Users can run specific tasks, such as test generation, across different programming languages to evaluate LLMs' language understanding and code generation capabilities.

Mutahunter is an open-source language-agnostic mutation testing tool maintained by CodeIntegrity. It leverages LLM models to inject context-aware faults into codebase, ensuring comprehensive testing. The tool aims to empower companies and developers to enhance test suites and improve software quality by verifying the effectiveness of test cases through creating mutants in the code and checking if the test cases can catch these changes. Mutahunter provides detailed reports on mutation coverage, killed mutants, and survived mutants, enabling users to identify potential weaknesses in their test suites.

Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency. It helps users improve AI output quality through data quality, take control of their data and models, and improve efficiency by quickly iterating on the right data and models. Argilla is an open-source community-driven project that provides tools for achieving and maintaining high-quality data standards, with a focus on NLP and LLMs. It is used by AI teams from companies like the Red Cross, Loris.ai, and Prolific to improve the quality and efficiency of AI projects.

AI-Driven Research Assistant is an advanced AI-powered system utilizing specialized agents for data analysis, visualization, and report generation. It integrates LangChain, OpenAI's GPT models, and LangGraph for complex research processes. Key features include hypothesis generation, data processing, web search, code generation, and report writing. The system's unique Note Taker agent maintains project state, reducing overhead and improving context retention. System requirements include Python 3.10+ and Jupyter Notebook environment. Installation involves cloning the repository, setting up a Conda virtual environment, installing dependencies, and configuring environment variables. Usage instructions include setting data, running Jupyter Notebook, customizing research tasks, and viewing results. Main components include agents for hypothesis generation, process supervision, visualization, code writing, search, report writing, quality review, and note-taking. Workflow involves hypothesis generation, processing, quality review, and revision. Customization is possible by modifying agent creation and workflow definition. Current issues include OpenAI errors, NoteTaker efficiency, runtime optimization, and refiner improvement. Contributions via pull requests are welcome under the MIT License.

FiftyOne is an open-source tool designed for building high-quality datasets and computer vision models. It supercharges machine learning workflows by enabling users to visualize datasets, interpret models faster, and improve efficiency. With FiftyOne, users can explore scenarios, identify failure modes, visualize complex labels, evaluate models, find annotation mistakes, and much more. The tool aims to streamline the process of improving machine learning models by providing a comprehensive set of features for data analysis and model interpretation.

Distilabel is a framework for synthetic data and AI feedback for AI engineers that require high-quality outputs, full data ownership, and overall efficiency. It helps you synthesize data and provide AI feedback to improve the quality of your AI models. With Distilabel, you can: * **Synthesize data:** Generate synthetic data to train your AI models. This can help you to overcome the challenges of data scarcity and bias. * **Provide AI feedback:** Get feedback from AI models on your data. This can help you to identify errors and improve the quality of your data. * **Improve your AI output quality:** By using Distilabel to synthesize data and provide AI feedback, you can improve the quality of your AI models and get better results.

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.

STORM is a LLM system that writes Wikipedia-like articles from scratch based on Internet search. While the system cannot produce publication-ready articles that often require a significant number of edits, experienced Wikipedia editors have found it helpful in their pre-writing stage. **Try out our [live research preview](https://storm.genie.stanford.edu/) to see how STORM can help your knowledge exploration journey and please provide feedback to help us improve the system 🙏!**

The AI Toolkit by Ostris is a collection of tools for machine learning, specifically designed for image generation, LoRA (latent representations of attributes) extraction and manipulation, and model training. It provides a user-friendly interface and extensive documentation to make it accessible to both developers and non-developers. The toolkit is actively under development, with new features and improvements being added regularly. Some of the key features of the AI Toolkit include: - Batch Image Generation: Allows users to generate a batch of images based on prompts or text files, using a configuration file to specify the desired settings. - LoRA (lierla), LoCON (LyCORIS) Extractor: Facilitates the extraction of LoRA and LoCON representations from pre-trained models, enabling users to modify and manipulate these representations for various purposes. - LoRA Rescale: Provides a tool to rescale LoRA weights, allowing users to adjust the influence of specific attributes in the generated images. - LoRA Slider Trainer: Enables the training of LoRA sliders, which can be used to control and adjust specific attributes in the generated images, offering a powerful tool for fine-tuning and customization. - Extensions: Supports the creation and sharing of custom extensions, allowing users to extend the functionality of the toolkit with their own tools and scripts. - VAE (Variational Auto Encoder) Trainer: Facilitates the training of VAEs for image generation, providing users with a tool to explore and improve the quality of generated images. The AI Toolkit is a valuable resource for anyone interested in exploring and utilizing machine learning for image generation and manipulation. Its user-friendly interface, extensive documentation, and active development make it an accessible and powerful tool for both beginners and experienced users.

MARS5 is a novel English speech model (TTS) developed by CAMB.AI, featuring a two-stage AR-NAR pipeline with a unique NAR component. The model can generate speech for various scenarios like sports commentary and anime with just 5 seconds of audio and a text snippet. It allows steering prosody using punctuation and capitalization in the transcript. Speaker identity is specified using an audio reference file, enabling 'deep clone' for improved quality. The model can be used via torch.hub or HuggingFace, supporting both shallow and deep cloning for inference. Checkpoints are provided for AR and NAR models, with hardware requirements of 750M+450M params on GPU. Contributions to improve model stability, performance, and reference audio selection are welcome.

Labelbox is a data-centric AI platform for enterprises to develop, optimize, and use AI to solve problems and power new products and services. Enterprises use Labelbox to curate data, generate high-quality human feedback data for computer vision and LLMs, evaluate model performance, and automate tasks by combining AI and human-centric workflows. The academic & research community uses Labelbox for cutting-edge AI research.

Reflection-Tuning is a project focused on improving the quality of instruction-tuning data through a reflection-based method. It introduces Selective Reflection-Tuning, where the student model can decide whether to accept the improvements made by the teacher model. The project aims to generate high-quality instruction-response pairs by defining specific criteria for the oracle model to follow and respond to. It also evaluates the efficacy and relevance of instruction-response pairs using the r-IFD metric. The project provides code for reflection and selection processes, along with data and model weights for both V1 and V2 methods.

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.

The 'awesome-deliberative-prompting' repository focuses on how to ask Large Language Models (LLMs) to produce reliable reasoning and make reason-responsive decisions through deliberative prompting. It includes success stories, prompting patterns and strategies, multi-agent deliberation, reflection and meta-cognition, text generation techniques, self-correction methods, reasoning analytics, limitations, failures, puzzles, datasets, tools, and other resources related to deliberative prompting. The repository provides a comprehensive overview of research, techniques, and tools for enhancing reasoning capabilities of LLMs.

Scientific expert in evaluating articles using ROBINS-I and Cochrane tools

Food quality inspection expert for analyzing food images.

Especialista em análise de qualidade e feedback em redes sociais.

It’s your first day! Excited, Nervous? Let me help you start off strong in your career. Type "help" for More Information

Expert in water filtration systems

Water Test Strip Analyst

Expert in biostatistics, psychometrics, and general statistical analysis.

Analyzes IR spectra, prompts for uploads, and details findings in tables.

Optimizes production processes for efficient large-scale operations.

Expert in 3D printing diagnostics and problem resolution, mindful of confidentiality and careful with brand usage.

Assistente para Teses e Dissertações de Engenharia de Minas

A software architect for C4 Model generation.

Formally evaluates clinical cases against CDC/NHSN HAI surveillance definition criteria

Formal Food Analysis Expert, providing professional insights.

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。

Improves product quality through innovative research and development.

AI tool for self-evaluating and enhancing scientific research capabilities.

Your AI research assistant, for turning a problem into a research, developing research questions, generating plans, analyzing data and improving research workflows for project success

Helps write and refine medical SCI papers with accuracy and research guidance.

生成操作流程的生物信息学 GPT