Best AI tools for< Scholars >

ScholarRoll is the first of its kind scholarship search tool that smartly matches you to millions of $'s in niche scholarships based on relevance and winning chances. Manage your entire scholarship journey in one secure platform with our comprehensive upto date database, Al powered search, tracking tool, and timely reminders.

Semantic Scholar is a free, AI-powered research tool for scientific literature. It is based at the Allen Institute for AI and provides access to over 217 million papers from all fields of science. Semantic Scholar uses AI to help users discover and explore scientific literature, and to stay up-to-date on the latest research. The tool also includes a number of features to help users manage their research, such as the ability to save papers, create bibliographies, and share research with others.

The Future of Privacy Forum (FPF) is an AI tool that serves as a catalyst for privacy leadership and scholarship, advancing principled data practices in support of emerging technologies. It provides resources, training sessions, and guidance on AI-related topics, online advertising, youth privacy legislation, and more. FPF brings together industry, academics, civil society, policymakers, and other stakeholders to explore challenges posed by emerging technologies and develop privacy protections, ethical norms, and best practices.

Tarteel is an AI-powered application designed to help users memorize the Quran more effectively. It offers features such as mistake detection, memorization planning, setting goals, and a premium experience. With Tarteel, users can tailor their memorization journey to their learning style and preferences, track their progress, and receive real-time alerts for missed, incorrect, and skipped words in their recitation. The application aims to provide a seamless and personalized Quran memorization experience for users of all levels.

AdmitGPT is a personal AI college application copilot powered by GPT-4. It offers tailored college recommendations, essay feedback, interview preparation, scholarship navigation, and user support to streamline the college application process for students, parents, educators, and counselors. AdmitGPT aims to save time for college applicants, provide expert guidance, and unlock paths to success in college admissions.

Ink to Ivy is an AI-powered writing companion that helps students elevate their college admissions essays. It provides personalized feedback, guidance, and suggestions to help students craft compelling, authentic narratives that meet each application's unique requirements. With real-time iterative improvement, students can refine their drafts to perfection.

Skimming is an AI tool that enables users to interact with various types of data, including audio, video, and text, to extract knowledge. It offers features like chatting with documents, YouTube videos, websites, audio, and video, as well as custom prompts and multilingual support. Skimming is trusted by over 100,000 users and is designed to save time and enhance information extraction. The tool caters to a diverse audience, including teachers, students, businesses, researchers, scholars, lawyers, HR professionals, YouTubers, and podcasters.

Kyros College Prep is an AI-assisted platform designed to help students with their college applications. The platform utilizes artificial intelligence to provide personalized guidance and support throughout the college application process. By leveraging AI technology, Kyros College Prep aims to streamline the application process, enhance the quality of applications, and increase students' chances of getting accepted into their desired colleges.

Salam Chat is an AI-powered chatbot application designed to help users learn about Islam more easily. It features a halal filter that provides citations to the Quran & Hadith, ensuring the accuracy and reliability of the information shared. The chatbot is volunteer-driven and open-source, with plans to implement more features in the future. It is a safe platform for kids as it filters out content outside the scope of Islam. The application is developed by the Minority Think Tank Foundation, aiming to create a ChatGPT alternative for the Muslim community.

StudentAI.app is an AI-powered platform that provides students, graduates, and professionals with a comprehensive suite of tools and resources to enhance their academic and career journeys. With over 100 AI-powered tools, 24/7 access to AI tutors, and a dedicated team of experts, StudentAI.app empowers users to master homework, research, job searches, scholarship applications, mock interviews, essay writing, and much more. The platform is designed to be user-friendly and accessible, with a focus on providing personalized support and guidance to help users achieve their goals.

Easy Islamic Dream Interpretation is an AI tool that offers dream interpretations based on Quranic verses, Hadith, and established Islamic principles. The tool draws insights from classical Islamic scholars like Ibn Sirin, Al-Nabulsi, and Ibn Kathir to provide accurate and meaningful interpretations of dreams. Users can gain a deeper understanding of their dreams through the lens of Islamic teachings and traditions.

Netwrck is an AI tool that offers AI Chat, AI Characters, and an AI Art Generator. Users can create unique AI characters, engage in voice chats, and generate art using AI technology. The platform provides a wide range of AI storytellers, scholars, artists, poets, diplomats, and more, allowing users to interact with diverse virtual personalities. Netwrck aims to provide an immersive and creative experience through AI-generated content.

Moxie is an AI-powered academic research writing companion that assists users in refining arguments, guiding research, and enhancing academic voice. It offers personalized feedback, AI-powered writing assistance, and tools for research design. Unlike AI content generators, Moxie empowers scholars to tackle complex tasks while preserving their critical thinking. The platform provides premium AI models, interactive learning sessions, and a personalized approach to academic writing. Users can streamline research processes, refine arguments, and receive actionable feedback to enhance their academic work.

O'Reilly Media is an AI-powered platform offering technology and business training for individuals, businesses, government, and higher education institutions. With over 5,000 companies relying on their digital courses, O'Reilly provides resources to upskill teams in tools and technologies driving business outcomes. The platform features courses, certifications, interactive learning, live events, and insights reporting. O'Reilly leverages generative AI tools and large language models to help employees stay ahead in their tech careers. The platform also offers diversity scholarships and awards to promote inclusivity and recognize excellence in technical learning. With a history of over 40 years, O'Reilly has been sharing knowledge through books, tech conferences, and online learning content.

Scholarcy is an AI-powered tool designed to help students and researchers summarize, analyze, and organize their research efficiently. It converts long and complex texts into interactive summary flashcards, highlights key information, and guides users to important sections of text. Scholarcy also offers features to enhance summaries, critically evaluate texts, organize knowledge, and synthesize insights. With compatibility across various file formats and sources, Scholarcy aims to revolutionize research workflows and save users valuable time.

ScholarAI is an AI-powered scientific research tool that offers a wide range of features to help users navigate and extract insights from scientific literature. With access to over 200 million peer-reviewed articles, ScholarAI allows users to conduct abstract searches, literature mapping, PDF reading, literature reviews, gap analysis, direct Q&A, table and figure extraction, citation management, and project management. The tool is designed to accelerate the research process and provide tailored scientific insights to users.

ArxivPaperAI is an AI-powered research paper summarizer that helps you quickly and easily understand the key points of academic papers. With ArxivPaperAI, you can:

Papertalk.io is an AI-powered platform that revolutionizes research by providing users with access to over 215 million papers, AI-generated explanations, and actionable insights. The platform offers precision search tools, AI-powered understanding of research papers, and personalized guidance on applying insights practically. Papertalk.io aims to make research more accessible and approachable for users from diverse backgrounds, transforming complex data into easy-to-digest formats to foster innovation and expertise.

Transcript.LOL is a transcription tool designed to save time and enhance productivity for creators and small to medium-sized businesses. It offers a platform to transcribe audio, video, and meeting recordings, supporting over 1500 platforms. The tool provides summaries, categorizes key themes, and offers contextual Q&A based on the transcriptions. With speaker identification and readable transcripts, users can easily navigate and understand the content. Transcript.LOL aims to streamline the transcription process and provide valuable insights faster than ever before.

RikiGPT is an AI tool designed for academic research, offering access to over 200 million scholarly sources. It provides enhanced writing experiences with detailed content, customizable reference lists, and integration with the latest GPT technology. Users can generate a 200-page thesis in just 1 minute, receive full academic chapters, and benefit from in-text citations and bibliography support. The tool also offers full translation services to over 100 languages, making it a comprehensive solution for research and writing needs.

LLM Learning Database is a comprehensive repository dedicated to AI large models, offering a curated collection of resources covering fundamental knowledge, cutting-edge technologies, and practical applications. It includes guides, case studies, code examples for model training, optimization, and deployment, as well as insightful articles from industry experts and scholars. Whether you are a beginner or an experienced learner in the field of AI large models, this repository aims to support your learning journey and foster continuous growth and progress.

LLMs4TS is a repository focused on the application of cutting-edge AI technologies for time-series analysis. It covers advanced topics such as self-supervised learning, Graph Neural Networks for Time Series, Large Language Models for Time Series, Diffusion models, Mixture-of-Experts architectures, and Mamba models. The resources in this repository span various domains like healthcare, finance, and traffic, offering tutorials, courses, and workshops from prestigious conferences. Whether you're a professional, data scientist, or researcher, the tools and techniques in this repository can enhance your time-series data analysis capabilities.

The Classical Language Toolkit (CLTK) is a Python library that provides natural language processing (NLP) capabilities for pre-modern languages. It offers a modular processing pipeline with pre-configured defaults and supports almost 20 languages. Users can install the latest version using pip and access detailed documentation on the official website. The toolkit is designed to meet the unique needs of researchers working with historical languages, filling a void in the NLP landscape that often neglects non-spoken languages and different research goals.

Welcome to our Awesome-llm-safety repository! We've curated a collection of the latest, most comprehensive, and most valuable resources on large language model safety (llm-safety). But we don't stop there; included are also relevant talks, tutorials, conferences, news, and articles. Our repository is constantly updated to ensure you have the most current information at your fingertips.

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

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.

Large Language Models (LLM) are used to browse the Wolfram directory and associated URLs to create the category structure and good word embeddings. The goal is to generate enriched prompts for GPT, Wikipedia, Arxiv, Google Scholar, Stack Exchange, or Google search. The focus is on one subdirectory: Probability & Statistics. Documentation is in the project textbook `Projects4.pdf`, which is available in the folder. It is recommended to download the document and browse your local copy with Chrome, Edge, or other viewers. Unlike on GitHub, you will be able to click on all the links and follow the internal navigation features. Look for projects related to NLP and LLM / xLLM. The best starting point is project 7.2.2, which is the core project on this topic, with references to all satellite projects. The project textbook (with solutions to all projects) is the core document needed to participate in the free course (deep tech dive) called **GenAI Fellowship**. For details about the fellowship, follow the link provided. An uncompressed version of `crawl_final_stats.txt.gz` is available on Google drive, which contains all the crawled data needed as input to the Python scripts in the XLLM5 and XLLM6 folders.

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.

Step-DPO is a method for enhancing long-chain reasoning ability of LLMs with a data construction pipeline creating a high-quality dataset. It significantly improves performance on math and GSM8K tasks with minimal data and training steps. The tool fine-tunes pre-trained models like Qwen2-7B-Instruct with Step-DPO, achieving superior results compared to other models. It provides scripts for training, evaluation, and deployment, along with examples and acknowledgements.

AirSLAM is an efficient visual SLAM system designed to tackle short-term and long-term illumination challenges. It combines deep learning techniques with traditional optimization methods, featuring a unified CNN for keypoint and structural line extraction. The system includes a relocalization pipeline for map reuse, accelerated using C++ and NVIDIA TensorRT. Outperforming other SLAM systems in challenging environments, it runs at 73Hz on PC and 40Hz on embedded platforms.

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

Academic_LLM_Sec_Papers is a curated collection of academic papers related to LLM Security Application. The repository includes papers sorted by conference name and published year, covering topics such as large language models for blockchain security, software engineering, machine learning, and more. Developers and researchers are welcome to contribute additional published papers to the list. The repository also provides information on listed conferences and journals related to security, networking, software engineering, and cryptography. The papers cover a wide range of topics including privacy risks, ethical concerns, vulnerabilities, threat modeling, code analysis, fuzzing, and more.

LLMGA (Multimodal Large Language Model-based Generation Assistant) is a tool that leverages Large Language Models (LLMs) to assist users in image generation and editing. It provides detailed language generation prompts for precise control over Stable Diffusion (SD), resulting in more intricate and precise content in generated images. The tool curates a dataset for prompt refinement, similar image generation, inpainting & outpainting, and visual question answering. It offers a two-stage training scheme to optimize SD alignment and a reference-based restoration network to alleviate texture, brightness, and contrast disparities in image editing. LLMGA shows promising generative capabilities and enables wider applications in an interactive manner.

MooER (摩耳) is an LLM-based speech recognition and translation model developed by Moore Threads. It allows users to transcribe speech into text (ASR) and translate speech into other languages (AST) in an end-to-end manner. The model was trained using 5K hours of data and is now also available with an 80K hours version. MooER is the first LLM-based speech model trained and inferred using domestic GPUs. The repository includes pretrained models, inference code, and a Gradio demo for a better user experience.

Paper-ai is a tool that helps you write papers using artificial intelligence. It provides features such as AI writing assistance, reference searching, and editing and formatting tools. With Paper-ai, you can quickly and easily create high-quality papers.

ShapeLLM is the first 3D Multimodal Large Language Model designed for embodied interaction, exploring a universal 3D object understanding with 3D point clouds and languages. It supports single-view colored point cloud input and introduces a robust 3D QA benchmark, 3D MM-Vet, encompassing various variants. The model extends the powerful point encoder architecture, ReCon++, achieving state-of-the-art performance across a range of representation learning tasks. ShapeLLM can be used for tasks such as training, zero-shot understanding, visual grounding, few-shot learning, and zero-shot learning on 3D MM-Vet.

CuMo is a project focused on scaling multimodal Large Language Models (LLMs) with Co-Upcycled Mixture-of-Experts. It introduces CuMo, which incorporates Co-upcycled Top-K sparsely-gated Mixture-of-experts blocks into the vision encoder and the MLP connector, enhancing the capabilities of multimodal LLMs. The project adopts a three-stage training approach with auxiliary losses to stabilize the training process and maintain a balanced loading of experts. CuMo achieves comparable performance to other state-of-the-art multimodal LLMs on various Visual Question Answering (VQA) and visual-instruction-following benchmarks.

Merlin is a groundbreaking model capable of generating natural language responses intricately linked with object trajectories of multiple images. It excels in predicting and reasoning about future events based on initial observations, showcasing unprecedented capability in future prediction and reasoning. Merlin achieves state-of-the-art performance on the Future Reasoning Benchmark and multiple existing multimodal language models benchmarks, demonstrating powerful multi-modal general ability and foresight minds.

EVE is an official PyTorch implementation of Unveiling Encoder-Free Vision-Language Models. The project aims to explore the removal of vision encoders from Vision-Language Models (VLMs) and transfer LLMs to encoder-free VLMs efficiently. It also focuses on bridging the performance gap between encoder-free and encoder-based VLMs. EVE offers a superior capability with arbitrary image aspect ratio, data efficiency by utilizing publicly available data for pre-training, and training efficiency with a transparent and practical strategy for developing a pure decoder-only architecture across modalities.

This repository contains the code for HOLD, a method that jointly reconstructs hands and objects from monocular videos without assuming a pre-scanned object template. It can reconstruct 3D geometries of novel objects and hands, enabling template-free bimanual hand-object reconstruction, textureless object interaction with hands, and multiple objects interaction with hands. The repository provides instructions to download in-the-wild videos from HOLD, preprocess and train on custom videos, a volumetric rendering framework, a generalized codebase for single and two hand interaction with objects, a viewer to interact with predictions, and code to evaluate and compare with HOLD in HO3D. The repository also includes documentation for setup, training, evaluation, visualization, preprocessing custom sequences, and using HOLD on ARCTIC.

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