Best AI tools for< Explain Research >

Explainpaper is an AI-powered tool designed to simplify the process of reading and understanding research papers. Users can upload a paper, highlight confusing text, and receive explanations using an AI model. The tool aims to make complex concepts more accessible and help researchers, students, and enthusiasts comprehend academic content more efficiently.

Kognitium is an AI assistant designed to provide users with comprehensive and accurate information across various domains. It is equipped with advanced capabilities that enable it to understand the intent behind user inquiries and deliver tailored responses. Kognitium's knowledge base spans a wide range of subjects, including current events, science, history, philosophy, and linguistics. It is designed to be user-friendly and accessible, making it a valuable tool for students, professionals, and anyone seeking to expand their knowledge. Kognitium is committed to providing reliable and actionable insights, empowering users to make informed decisions and enhance their understanding of the world around them.

SiteExplainer is an AI-powered web application that helps users understand the purpose of any website quickly and accurately. It uses advanced artificial intelligence and machine learning technology to analyze the content of a website and present a summary of the main ideas and key points. SiteExplainer simplifies the language used on landing pages and eliminates corporate jargon to help visitors better understand a website's content.

Memenome AI is an AI tool that helps users discover and understand trending sounds, hashtags, accounts, and posts on TikTok. It offers features to find top sounds, hashtags, and posts, provides AI analysis and templates for trend understanding, and allows users to iterate through content ideas with Meme0. The tool aims to save users time by efficiently identifying trends and empowering them to create engaging content.

HyperWrite is an AI writing assistant that helps users write, research, and collaborate. It offers a range of tools, including AutoWrite, Summarizer, Explain Like I'm 5, Rewrite Content, Email Responder, Magic Editor, AI Speech Writer, AI Writer, Scholar AI, and more. HyperWrite can be used for a variety of tasks, including writing emails, articles, social media posts, website content, and more. It can also be used to summarize text, simplify complex topics, rewrite content, and generate speeches.

MaxAI.me is an AI application that offers a suite of AI-powered tools to supercharge reading, writing, and searching across the web. It provides features such as AI summary, reading assistant, vision, rewriter, instant reply, chat, search, translator, prompts, and art. MaxAI.me caters to various industries including business owners, marketing, education, consulting, human resources, financial services, and real estate. Additionally, it offers free online PDF tools for merging, splitting, converting to PNG/JPEG, and more. Users can access MaxAI.me via Chrome and Edge extensions for free.

ChatDOC is an AI-powered tool that allows users to chat with PDF documents and get instant answers with cited sources. It can summarize long documents, explain complex concepts, and find key information in seconds. ChatDOC is built for professionals and is used by over 500,000 global users.

Tooltips.ai is an AI-powered reading extension that provides instant definitions, translations, and summaries for any word or phrase you hover over. It is designed to enhance your reading experience by making it easier and faster to understand complex or unfamiliar content. Tooltips.ai integrates seamlessly with your browser, so you can use it on any website or document.

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

Sider is an AI tool that combines ChatGPT Sidebar with GPT-4o, Claude 3, and Gemini 1.5 to provide an all-in-one AI assistant for reading, writing, and chatting on any webpage. It offers features such as chat support with links, images, PDFs, and various GPT models, free usage, and integration with Chrome. Users can benefit from increased productivity, reduced time spent on tasks, and enhanced creativity and knowledge expansion.

Flot AI is an AI-powered writing, reading, and memorization tool that seamlessly integrates into your daily workflow. It is backed by OpenAI and designed to assist users across various apps and websites. With features like AI memory, grammar correction, composing drafts, and expert prompts, Flot AI aims to enhance users' productivity and creativity. The application supports over 200 languages and offers a universal solution for writing and memory tasks at a competitive price point.

MaxAI is a productivity tool that provides users with access to various AI models, including ChatGPT, Claude, and Gemini, through a single platform. It offers a range of AI-powered features such as AI chat, AI rewriter, AI quick reply, AI summary, AI search, AI art, and AI translator. MaxAI is designed to help users save time and improve their productivity by automating repetitive tasks and providing assistance with various tasks.

AskDocs is an AI-powered document assistant designed to help users read faster and create better work content. It offers cross-document analysis, quick answers linked to documents, one-click summaries of key concepts, and the ability to understand confusing information. With a focus on enhancing productivity, AskDocs is trusted by students, knowledge workers, and small businesses to streamline research, meeting notes, emails, and more. The tool supports various document types and provides instant answers directly linked to sources within the uploaded documents.

ExplainThis is an AI-powered assistant that helps you understand the web. It can explain key concepts, summarize content, and provide context without leaving the webpage. With ExplainThis, you can learn and grow while you browse, making your daily browsing more informative and efficient.

Messy Desk is an AI-powered personal knowledge library application that facilitates social learning. It offers features such as Smart Preview for summarizing documents, Powerful Search with semantic capabilities, AI Explanations for complex topics, Interactive Chat for instant answers, and Community Discussion for sharing insights. Users can easily upload PDFs or URLs to build their library and engage in collaborative learning.

Chat-docs AI is an innovative AI application that allows users to interact with PDF documents through natural language conversations. The tool leverages advanced artificial intelligence algorithms to summarize long documents, explain complex concepts, and find key information with cited sources in seconds. It transforms PDFs into intelligent entities capable of dialogue, making learning, research, and analysis more interactive and personalized. Chat-docs AI is designed to be intuitive, secure, and accessible to users from various backgrounds, revolutionizing the way individuals engage with textual content.

Mathly is an AI-powered homework help tool that enables students to learn in a better, smarter, and faster way. By using AI technology, Mathly can solve math problems, provide explanations, generate practice problems, and personalize learning experiences based on the user's learning style. It aims to revolutionize the way students approach homework and understanding mathematical concepts.

AI Does Your Homework is an innovative AI tool designed to assist students with their homework assignments. The tool utilizes advanced artificial intelligence algorithms to provide accurate solutions to a wide range of academic questions and problems. Students can simply input their questions into the tool, and it will generate step-by-step solutions, explanations, and answers in real-time. AI Does Your Homework aims to streamline the learning process, enhance understanding of complex topics, and improve academic performance.

curioAI is an AI tool that offers a one-stop knowledge platform powered by artificial intelligence. Users can sign in with Google to access a wide range of information on various topics, from artificial intelligence and black holes to mental health and memes. The tool helps users generate engaging tweets and LinkedIn posts, unlock new professional opportunities, and gain deep understanding on complex topics in simple terms. With the power of AI, curioAI aims to provide users with new insights, ideas, and original songs to enhance their knowledge and creativity.

AI Homework Helper is an innovative platform powered by artificial intelligence technology, designed to assist students with their homework assignments across various subjects. Our AI Homework Helper analyzes students’ homework requirements and generates customized solutions, including step-by-step explanations, relevant examples, and problem-solving strategies. Our platform features a user-friendly interface that makes it easy for students to navigate and access the assistance they need, without any technical hassles.

GPT Researcher is an autonomous agent designed for comprehensive online research on a variety of tasks. It can produce detailed, factual, and unbiased research reports with customization options. The tool addresses issues of speed, determinism, and reliability by leveraging parallelized agent work. The main idea involves running 'planner' and 'execution' agents to generate research questions, seek related information, and create research reports. GPT Researcher optimizes costs and completes tasks in around 3 minutes. Features include generating long research reports, aggregating web sources, an easy-to-use web interface, scraping web sources, and exporting reports to various formats.

InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...

imodelsX is a Scikit-learn friendly library that provides tools for explaining, predicting, and steering text models/data. It also includes a collection of utilities for getting started with text data. **Explainable modeling/steering** | Model | Reference | Output | Description | |---|---|---|---| | Tree-Prompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/tree_prompt) | Explanation + Steering | Generates a tree of prompts to steer an LLM (_Official_) | | iPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/iprompt) | Explanation + Steering | Generates a prompt that explains patterns in data (_Official_) | | AutoPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/autoprompt) | Explanation + Steering | Find a natural-language prompt using input-gradients (⌛ In progress)| | D3 | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/d3) | Explanation | Explain the difference between two distributions | | SASC | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/sasc) | Explanation | Explain a black-box text module using an LLM (_Official_) | | Aug-Linear | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_linear) | Linear model | Fit better linear model using an LLM to extract embeddings (_Official_) | | Aug-Tree | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_tree) | Decision tree | Fit better decision tree using an LLM to expand features (_Official_) | **General utilities** | Model | Reference | |---|---| | LLM wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/llm) | Easily call different LLMs | | | Dataset wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/data) | Download minimially processed huggingface datasets | | | Bag of Ngrams | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/bag_of_ngrams) | Learn a linear model of ngrams | | | Linear Finetune | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/linear_finetune) | Finetune a single linear layer on top of LLM embeddings | | **Related work** * [imodels package](https://github.com/microsoft/interpretml/tree/main/imodels) (JOSS 2021) - interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible). * [Adaptive wavelet distillation](https://arxiv.org/abs/2111.06185) (NeurIPS 2021) - distilling a neural network into a concise wavelet model * [Transformation importance](https://arxiv.org/abs/1912.04938) (ICLR 2020 workshop) - using simple reparameterizations, allows for calculating disentangled importances to transformations of the input (e.g. assigning importances to different frequencies) * [Hierarchical interpretations](https://arxiv.org/abs/1807.03343) (ICLR 2019) - extends CD to CNNs / arbitrary DNNs, and aggregates explanations into a hierarchy * [Interpretation regularization](https://arxiv.org/abs/2006.14340) (ICML 2020) - penalizes CD / ACD scores during training to make models generalize better * [PDR interpretability framework](https://www.pnas.org/doi/10.1073/pnas.1814225116) (PNAS 2019) - an overarching framewwork for guiding and framing interpretable machine learning

This repository contains frontier research on explainable AI (XAI), a hot topic in the field of artificial intelligence. It includes trends, use cases, survey papers, books, open courses, papers, and Python libraries related to XAI. The repository aims to organize and categorize publications on XAI, provide evaluation methods, and list various Python libraries for explainable AI.

Chat Your Doc is an experimental project exploring various applications based on LLM technology. It goes beyond being just a chatbot project, focusing on researching LLM applications using tools like LangChain and LlamaIndex. The project delves into UX, computer vision, and offers a range of examples in the 'Lab Apps' section. It includes links to different apps, descriptions, launch commands, and demos, aiming to showcase the versatility and potential of LLM applications.

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.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

This repository, named Awesome-Embodied-Agent-with-LLMs, is a curated list of research related to Embodied AI or agents with Large Language Models. It includes various papers, surveys, and projects focusing on topics such as self-evolving agents, advanced agent applications, LLMs with RL or world models, planning and manipulation, multi-agent learning and coordination, vision and language navigation, detection, 3D grounding, interactive embodied learning, rearrangement, benchmarks, simulators, and more. The repository provides a comprehensive collection of resources for individuals interested in exploring the intersection of embodied agents and large language models.

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.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

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.

Awesome LLM is a curated list of resources related to Large Language Models (LLMs), including models, projects, datasets, benchmarks, materials, papers, posts, GitHub repositories, HuggingFace repositories, and reading materials. It provides detailed information on various LLMs, their parameter sizes, announcement dates, and contributors. The repository covers a wide range of LLM-related topics and serves as a valuable resource for researchers, developers, and enthusiasts interested in the field of natural language processing and artificial intelligence.

This repository is a collection of papers focused on understanding the internal mechanism of large language models (LLM). It includes research on topics such as how LLMs handle multilingualism, learn in-context, and handle factual associations. The repository aims to provide insights into the inner workings of transformer-based language models through a curated list of papers and surveys.

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.

Awesome-Attention-Heads is a platform providing the latest research on Attention Heads, focusing on enhancing understanding of Transformer structure for model interpretability. It explores attention mechanisms for behavior, inference, and analysis, alongside feed-forward networks for knowledge storage. The repository aims to support researchers studying LLM interpretability and hallucination by offering cutting-edge information on Attention Head Mining.

Awesome-Papers-Autonomous-Agent is a curated collection of recent papers focusing on autonomous agents, specifically interested in RL-based agents and LLM-based agents. The repository aims to provide a comprehensive resource for researchers and practitioners interested in intelligent agents that can achieve goals, acquire knowledge, and continually improve. The collection includes papers on various topics such as instruction following, building agents based on world models, using language as knowledge, leveraging LLMs as a tool, generalization across tasks, continual learning, combining RL and LLM, transformer-based policies, trajectory to language, trajectory prediction, multimodal agents, training LLMs for generalization and adaptation, task-specific designing, multi-agent systems, experimental analysis, benchmarking, applications, algorithm design, and combining with RL.

This repository is a collection of papers and resources related to Lifelong Learning of Large Language Model (LLM) based Agents. It focuses on continual learning and incremental learning of LLM agents, identifying key modules such as Perception, Memory, and Action. The repository serves as a roadmap for understanding lifelong learning in LLM agents and provides a comprehensive overview of related research and surveys.

WDoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It supports querying tens of thousands of documents simultaneously, offers tailored summaries to efficiently manage large amounts of information, and includes features like supporting multiple file types, various LLMs, local and private LLMs, advanced RAG capabilities, advanced summaries, trust verification, markdown formatted answers, sophisticated embeddings, extensive documentation, scriptability, type checking, lazy imports, caching, fast processing, shell autocompletion, notification callbacks, and more. WDoc is ideal for researchers, students, and professionals dealing with extensive information sources.

TruLens provides a set of tools for developing and monitoring neural nets, including large language models. This includes both tools for evaluation of LLMs and LLM-based applications with _TruLens-Eval_ and deep learning explainability with _TruLens-Explain_. _TruLens-Eval_ and _TruLens-Explain_ are housed in separate packages and can be used independently.

This repository provides a comprehensive survey of research papers on large language model (LLM)-based game agents. LLMs are powerful AI models that can understand and generate human language, and they have shown great promise for developing intelligent game agents. This survey covers a wide range of topics, including adventure games, crafting and exploration games, simulation games, competition games, cooperation games, communication games, and action games. For each topic, the survey provides an overview of the state-of-the-art research, as well as a discussion of the challenges and opportunities for future work.

Explains Arxiv papers with examples, analogies, and direct PDF links.

論文のPDFをアップロードすると、内容を日本語で分かりやすく説明します（OpenAI側の問題により、論文URLでの解説機能は一時停止しています）。This is the Japanese version of Paper Interpreter. The international version is available at https://chat.openai.com/g/g-R9Dry2N5h-paper-interpreter

Expert in explaining data visuals for academic publishing.

I explain AI papers in Chinese.

Explain scientific papers using the 3-pass method for efficient understanding. After uploading a paper, you can enter First pass/Second pass /Third pass / Q&A to get different level of response from SciPlore.

I explain terms in short accurately.

I simplify and explain AI concepts.

⚖️ Explain Asimov's Three Laws of Robotics

I'm a BSc tutor, here to explain complex concepts and guide you in science subjects.

Explain using math and python

An expert in classical mechanics who can explain and solve any classical mechanics problem. Specializes in Hamiltonian and Lagrangian mechanics.

I can quickly explain UX to Designers of any age. Let the UX'ing begin!

I'm a fluid mechanics tutor, ready to explain concepts and guide you through problems!

A Global dictionary that requires only a word to explain it in both english and its original language.

I offer engaging Python puzzles, explain solutions and immediately present the next challenge.

A biophysics research specialist for academic discussions.

I explain surname meanings and create images that resonate with them.

Expert math tutor and problem solver with online research and data analysis skills.

Expert in AI legal research by Prof. Kiskinov, SJD

Solves homework from photos, explains steps, and researches for accuracy.