Best AI tools for< Present Research Findings >

DMLR (Data-centric Machine Learning Research) is an AI tool that focuses on advancing research in data-centric machine learning. It organizes workshops, research retreats, maintains a journal, and runs a working group to support infrastructure projects. The platform covers topics such as data collection, governance, bias, and drifts, as well as data-centric explainable AI and AI alignment. DMLR encourages submissions around the theme of AI for Science, using AI to tackle scientific challenges and accelerate discoveries.

ResearchBuddy is an AI tool designed to automate the process of conducting literature reviews. It helps researchers and students efficiently gather and analyze information from various sources to enhance their research projects. By leveraging artificial intelligence, ResearchBuddy streamlines the review process, saving users time and effort. The platform offers a user-friendly interface and advanced algorithms to deliver accurate and relevant results. With ResearchBuddy, users can access a comprehensive database of scholarly articles and publications, making it easier to stay up-to-date with the latest research trends and findings.

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.

MindpoolAI is a tool that allows users to access multiple leading AI models with a single query. This means that users can get the answers they are looking for, spark ideas, and fuel their work, creativity, and curiosity. MindpoolAI is easy to use and does not require any technical expertise. Users simply need to enter their prompt and select the AI models they want to compare. MindpoolAI will then send the query to the selected models and present the results in an easy-to-understand format.

Google Patents is a search engine that allows users to search through the full text of patents that have been granted by the United States Patent and Trademark Office (USPTO). The database includes patents from 1790 to the present day, and users can search by keyword, inventor, assignee, or patent number. Google Patents also provides access to images of the original patent documents, as well as links to related patents and articles.

NovaResp cMAP™ is an AI-powered platform software designed to improve adherence to Continuous Positive Airway Pressure (CPAP) therapy for sleep apnea patients. It utilizes artificial intelligence and machine learning to predict and prevent apnea episodes during therapy, delivering personalized treatment at more comfortable air pressure levels. The application aims to enhance patient quality of life, increase sales for device manufacturers, and reduce labor costs for DMEs. NovaResp cMAP™ is compatible with all major PAP machines and is a revolutionary solution in the treatment of Obstructive Sleep Apnea (OSA).

ROSS Intelligence is a legal tech platform that leverages artificial intelligence to provide legal research solutions. It offers a comprehensive collection of statutes, regulations, and legal resources for all 50 states in the U.S. The platform enables legal professionals to conduct efficient and accurate legal research, stay updated on the latest legal news, and access AI-powered tools for enhancing their legal practice.

Pontus is an AI tool that enables users to build AI models with trust, manage risk, and ensure compliance effortlessly. It offers features like smart anonymization, rapid audit, and liability reduction, along with privacy-enhancing technology. Pontus allows for on-premise deployment, role-based access controls, and toxicity checking to prevent inappropriate content. The application is designed to work seamlessly with common LLM providers, making it a valuable asset for industries like healthcare, finance, and research.

Zelma is an AI-powered research assistant that enables users to find, graph, and understand U.S. school testing data using plain English queries. It allows users to search student test data by school district, demographics, grade, and more, and presents the results with graphs, tables, and descriptions. Zelma aims to make education data accessible and understandable for everyone.

UseScraper is a web crawler and scraper API that allows users to extract data from websites for research, analysis, and AI applications. It offers features such as full browser rendering, markdown conversion, and automatic proxies to prevent rate limiting. UseScraper is designed to be fast, easy to use, and cost-effective, with plans starting at $0 per month.

Paraphrasing.io is a free AI paraphrasing tool that helps users rewrite, edit, and adjust the tone of their content for improved comprehension. It prevents plagiarism in various types of content such as blogs, research papers, and more using cutting-edge AI technology. The tool offers four paraphrasing modes to cater to different writing styles and resonates with a distinct writing style. Users including writers, bloggers, researchers, students, and laypersons can benefit from this online tool to enhance the uniqueness, engagement, and readability of their content.

Chat EQ is an AI-powered application designed to help individuals develop conflict resolution skills for handling difficult conversations in personal and professional settings. The app draws upon decades of research in conflict resolution to provide users with research-based feedback and guidance. By using natural language input, Chat EQ offers insights into users' emotional and physical states, suggests conversation strategies, and aims to help users reach mutually beneficial outcomes while avoiding common pitfalls that can escalate conflicts.

Empler AI Inc is a website offering AI-powered products and services, including application programming interfaces, software tools, developer services, and documentation. The site collects Personal Information for various purposes, such as providing, analyzing, and improving services, conducting research, and ensuring security. Empler AI respects user privacy and complies with legal obligations. The site also offers aggregated information for analysis and research. Users can contact support for information updates or privacy rights. Empler AI implements security measures to protect Personal Information and may transfer data internationally.

SDXL Turbo is a cutting-edge text-to-image generation model that leverages Adversarial Diffusion Distillation (ADD) technology for high-quality, real-time image synthesis. Developed by Stability AI, SDXL Turbo is a distilled version of the SDXL 1.0 model, specifically trained for real-time synthesis. It excels in generating photorealistic images from text prompts in a single network evaluation, making it ideal for applications demanding speed and efficiency, such as video games, virtual reality, and instant content creation. SDXL Turbo is accessible to both professionals and hobbyists alike, with simple setup requirements and an intuitive interface. It presents unparalleled opportunities for research and development in advanced AI and image synthesis.

Storydoc is an AI-powered presentation tool that allows users to easily create stunning, interactive decks to increase engagement. With a variety of templates and features, Storydoc helps users bring their stories to life and win more customers. The platform offers tools for creating pitch decks, sales decks, proposals, reports, brochures, white papers, EPKs, business plans, one pagers, e-books, and more. Users can generate their decks with AI, edit them with automatic slide copy and design, and turbo-charge them with integrations. Storydoc also provides real-time deck analytics, personalized versions, and a community of creators for support and inspiration.

Storydoc is an AI-powered platform that allows users to easily create stunning and interactive decks to increase engagement. Trusted by top businesses, Storydoc helps business professionals simplify complex content, deliver rich and engaging presentations, and initiate new conversations with prospects. With features like AI-generated deck creation, automatic slide design adjustments, and real-time deck analytics, Storydoc empowers users to stand out, win more customers, and turbo-charge their presentations. Join a community of creators who have experienced the benefits of Storydoc in saving time, creating professional presentations, and engaging customers effectively.

Pitch is a presentation software designed for fast-moving teams. It offers a range of features to help users create, edit, and share presentations quickly and easily. Pitch also includes AI-powered tools to help users generate content and design slides. With Pitch, teams can collaborate on presentations in real time, track engagement, and get insights into how their presentations are performing.

Meetly AI is an AI-powered tool that helps you take meeting notes and action items. It uses natural language processing to understand the context of your meetings and generate accurate and comprehensive notes. Meetly AI also integrates with your calendar and other tools to make it easy to stay organized and on top of your tasks.

The website offers a captivating suite of AI-powered chatbot apps designed to enrich knowledge and spark curiosity. Users can chat with a wide range of Biblical figures, historical figures, famous authors, poets, playwrights, and philosophers from around the world. The apps are available for Apple, Android, Mac, and PC devices. The AI technology allows users to have conversations with these figures, providing a unique and engaging experience for users interested in history, literature, and spirituality.

JobXRecruiter is an AI-powered CV review tool designed for recruiters to streamline the candidate evaluation process. It automates the review of resumes, provides detailed candidate analysis, and helps recruiters save time by focusing on hiring rather than manual screening. The tool offers a 1-minute setup, reduces candidate evaluation time, and eliminates tedious screening tasks. With JobXRecruiter, recruiters can create projects for each vacancy, receive match scores for candidates, and easily shortlist the best candidates without opening individual CVs. The application is secure, efficient, and a game-changer for recruiters looking to optimize their hiring process.

CrewAI is a cutting-edge framework designed to orchestrate role-playing autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. It enables AI agents to assume roles, share goals, and operate in a cohesive unit, much like a well-oiled crew. Whether you're building a smart assistant platform, an automated customer service ensemble, or a multi-agent research team, CrewAI provides the backbone for sophisticated multi-agent interactions. With features like role-based agent design, autonomous inter-agent delegation, flexible task management, and support for various LLMs, CrewAI offers a dynamic and adaptable solution for both development and production workflows.

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 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.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

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.

Awesome-LLM-in-Social-Science is a repository that compiles papers evaluating Large Language Models (LLMs) from a social science perspective. It includes papers on evaluating, aligning, and simulating LLMs, as well as enhancing tools in social science research. The repository categorizes papers based on their focus on attitudes, opinions, values, personality, morality, and more. It aims to contribute to discussions on the potential and challenges of using LLMs in social science research.

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.

This competition is organized by Javier Rando and Florian Tramèr from the ETH AI Center and SPY Lab at ETH Zurich. The goal of the competition is to create a method that can detect universal backdoors in aligned language models. A universal backdoor is a secret suffix that, when appended to any prompt, enables the model to answer harmful instructions. The competition provides a set of poisoned generation models, a reward model that measures how safe a completion is, and a dataset with prompts to run experiments. Participants are encouraged to use novel methods for red-teaming, automated approaches with low human oversight, and interpretability tools to find the trojans. The best submissions will be offered the chance to present their work at an event during the SaTML 2024 conference and may be invited to co-author a publication summarizing the competition results.

ChatGPT Queue Prompts is a collection of prompt chains designed to enhance interactions with large language models like ChatGPT. These prompt chains help build context for the AI before performing specific tasks, improving performance. Users can copy and paste prompt chains into the ChatGPT Queue extension to process prompts in sequence. The repository includes example prompt chains for tasks like conducting AI company research, building SEO optimized blog posts, creating courses, revising resumes, enriching leads for CRM, personal finance document creation, workout and nutrition plans, marketing plans, and more.

This repository compiles a list of academic papers that evaluate, align, simulate, and provide surveys or perspectives on the use of Large Language Models (LLMs) in the field of Social Science. The papers cover various aspects of LLM research, including assessing their alignment with human values, evaluating their capabilities in tasks such as opinion formation and moral reasoning, and exploring their potential for simulating social interactions and addressing issues in diverse fields of Social Science. The repository aims to provide a comprehensive resource for researchers and practitioners interested in the intersection of LLMs and Social Science.

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.

TempCompass is a benchmark designed to evaluate the temporal perception ability of Video LLMs. It encompasses a diverse set of temporal aspects and task formats to comprehensively assess the capability of Video LLMs in understanding videos. The benchmark includes conflicting videos to prevent models from relying on single-frame bias and language priors. Users can clone the repository, install required packages, prepare data, run inference using examples like Video-LLaVA and Gemini, and evaluate the performance of their models across different tasks such as Multi-Choice QA, Yes/No QA, Caption Matching, and Caption Generation.

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.

ShieldLM is a bilingual safety detector designed to detect safety issues in LLMs' generations. It aligns with human safety standards, supports customizable detection rules, and provides explanations for decisions. Outperforming strong baselines, ShieldLM is impressive across 4 test sets.

Research Proposal Assistant Pro is designed to provide tailored assistance in research writing.

Research topic identifier for graduate students, providing detailed, academic-style problem outlines. (e.g. prompt: suggest research topics in renewable energy)

Teaches and analyzes research methods with in-depth, academic insights.

The AI mentor for medical education research

专注于计算机科学与技术论文指导的老师

A seasoned Market Research Director specializing in qualitative analysis.

全方位研究计划指导，提供示例，中英双语沟通。

Especialista em Engenharia de Materiais e Metalúrgica

Explore all French UFO sightings with a bilingual expert in GEIPAN's data analysis and insights.

Especialista em Teses e Dissertações de Farmácia

High School Science Research Mentor

A GPT trained on Memia newsletter archive 2020-present

Delving deep into classical music lore, past and present.

EXPERIMENT - Friendly expert on NYC dog license data from 2015-2016, with info on names, breeds and boroughs

Gathers and presents info on global wars in a table format with donation options.

Educates on historical genocides, emphasizing classical liberal values

Text & Image Pest Identifier with Q&A

AI Assistant for Legal CPD & ERP System Security

This GPT helps you understand and apply the MITRE ATT&CK Framework, whether you are familiar with the concepts or not.