Best AI tools for< Research Llm Safety >

Adversa AI is a platform that provides Secure AI Awareness, Assessment, and Assurance solutions for various industries to mitigate AI risks. The platform focuses on LLM Security, Privacy, Jailbreaks, Red Teaming, Chatbot Security, and AI Face Recognition Security. Adversa AI helps enable AI transformation by protecting it from cyber threats, privacy issues, and safety incidents. The platform offers comprehensive research, advisory services, and expertise in the field of AI security.

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.

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.

Lore macOS GPT-LLM Playground is an AI tool designed for macOS users, offering a Multi-Model Time Travel Versioning Combinatorial Runs Variants Full-Text Search Model-Cost Aware API & Token Stats Custom Endpoints Local Models Tables. It provides a user-friendly interface with features like Syntax, LaTeX Notes Export, Shortcuts, Vim Mode, and Sandbox. The tool is built with Cocoa, SwiftUI, and SQLite, ensuring privacy and offering support & feedback.

Every AI is an AI software that offers over 120 AI models, including ChatGPT from OpenAI and Anthropic/Claude, for a wide range of applications. It provides incredible speeds and access to all models for a subscription fee of $20. The platform aims to simplify AI development at scale by offering developer-friendly solutions with extensive documentation and SDKs for popular programming languages like Ruby and JavaScript.

Firecrawl is an advanced web crawling and data conversion tool designed to transform any website into clean, LLM-ready markdown. It automates the collection, cleaning, and formatting of web data, streamlining the preparation process for Large Language Model (LLM) applications. Firecrawl is best suited for business websites, documentation, and help centers, offering features like crawling all accessible subpages, handling dynamic content, converting data into well-formatted markdown, and more. It is built by LLM engineers for LLM engineers, providing clean data the way users want it.

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.

DeepSeek v3 is an advanced AI language model that represents a major breakthrough in AI language models. It features a groundbreaking Mixture-of-Experts (MoE) architecture with 671B total parameters, delivering state-of-the-art performance across various benchmarks while maintaining efficient inference capabilities. DeepSeek v3 is pre-trained on 14.8 trillion high-quality tokens and excels in tasks such as text generation, code completion, and mathematical reasoning. With a 128K context window and advanced Multi-Token Prediction, DeepSeek v3 sets new standards in AI language modeling.

Speck is a web automation tool that simplifies web data extraction using AI technology. It allows users to record their workflows and then automate the process with the help of an AI copilot. Speck learns from user interactions, ensuring efficient data extraction without the need for constant manual adjustments. The tool offers features such as custom workflow automation, web data supercharger, smart browser navigation, intelligent form filler, and interactive web tutorials. Speck is designed to streamline web tasks and enhance productivity by automating repetitive processes.

Derwen is an open-source integration platform for production machine learning in enterprise, specializing in natural language processing, graph technologies, and decision support. It offers expertise in developing knowledge graph applications and domain-specific authoring. Derwen collaborates closely with Hugging Face and provides strong data privacy guarantees, low carbon footprint, and no cloud vendor involvement. The platform aims to empower AI engineers and domain experts with quality, time-to-value, and ownership since 2017.

Cantian AI is an AI tool designed for the intelligent era. It offers advanced capabilities that require JavaScript to be enabled for optimal performance. The tool leverages artificial intelligence to provide users with intelligent solutions and insights.

AiPlus is an AI tool designed to serve as a cost-efficient model gateway. It offers users a platform to access and utilize various AI models for their projects and tasks. With AiPlus, users can easily integrate AI capabilities into their applications without the need for extensive development or resources. The tool aims to streamline the process of leveraging AI technology, making it accessible to a wider audience.

Genie TechBio is the world's first AI bioinformatician, offering an LLM-powered omics analysis software that operates entirely in natural language, eliminating the need for coding. Researchers can effortlessly analyze extensive datasets by engaging in a conversation with Genie, receiving recommendations for analysis pipelines, and obtaining results. The tool aims to accelerate biomedical research and empower scientists with newfound data analysis capabilities.

AnythingLLM is an all-in-one AI application designed for everyone. It offers a suite of tools for working with LLM (Large Language Models), documents, and agents in a fully private environment. Users can install AnythingLLM on their desktop for Windows, MacOS, and Linux, enabling flexible one-click installation and secure, fully private operation without internet connectivity. The application supports custom models, including enterprise models like GPT-4, custom fine-tuned models, and open-source models like Llama and Mistral. AnythingLLM allows users to work with various document formats, such as PDFs and word documents, providing tailored solutions with locally running defaults for privacy.

Tavily is an AI-powered research assistant that helps users gather information from multiple online sources and organize it into comprehensive research reports. It uses advanced algorithms and models to ensure the accuracy of the information provided and can be integrated with any LLM. Tavily is suitable for both individuals and enterprises who need to conduct research to make unbiased and informed decisions.

Goover is a personalized AI research agent that streamlines the process of acquiring knowledge by providing self-driving experiences. It offers users the ability to dive deeper into various topics through curated briefings, reports, and insights. Goover utilizes advanced AI technology to deliver tailored answers, identify key information, and facilitate meaningful discussions. Users can access knowledge anytime, anywhere through the mobile app, ensuring they stay informed and engaged with their passions. With Goover, users can track specific topics, receive automatic updates, and explore diverse perspectives effortlessly.

Flow AI is an advanced AI tool designed for evaluating and improving Large Language Model (LLM) applications. It offers a unique system for creating custom evaluators, deploying them with an API, and developing specialized LMs tailored to specific use cases. The tool aims to revolutionize AI evaluation and model development by providing transparent, cost-effective, and controllable solutions for AI teams across various domains.

Officely AI is an AI application that offers a platform for users to access and utilize various LLM (Large Language Model) models. Users can let these models interact with each other and integrate seamlessly. The platform provides tools, use cases, channels, and pricing options for users to explore and leverage the power of AI in their processes.

Cameron Jones is an AI tool developed by a Cognitive Science PhD student focusing on persuasion, deception, and social intelligence in humans and Large Language Models (LLMs). The tool analyzes LLM performance on tasks like the False Belief task and the Turing test. It also compares humans and LLMs on theory of mind evaluation. Cameron Jones provides select publications, recent media, and projects related to understanding, grounding, and reference in LLMs.

Vellum AI is an AI platform that supports using Microsoft Azure hosted OpenAI models. It offers tools for prompt engineering, semantic search, prompt chaining, evaluations, and monitoring. Vellum enables users to build AI systems with features like workflow automation, document analysis, fine-tuning, Q&A over documents, intent classification, summarization, vector search, chatbots, blog generation, sentiment analysis, and more. The platform is backed by top VCs and founders of well-known companies, providing a complete solution for building LLM-powered applications.

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.

Awesome ML is a curated list of resources and tools related to machine learning, covering a wide range of topics such as large language models, image models, video models, audio models, and marketing data science. It includes open LLM models, tools, GUIs, backends, voice assistants, code generation, libraries, fine tuning, data sets, research, image and video models, audio tasks like compression, speech recognition, and music generation, as well as resources for marketing data science. The repository aims to provide a comprehensive collection of resources for individuals interested in machine learning and its applications.

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.

The 'llm-misinformation-survey' repository is dedicated to the survey on combating misinformation in the age of Large Language Models (LLMs). It explores the opportunities and challenges of utilizing LLMs to combat misinformation, providing insights into the history of combating misinformation, current efforts, and future outlook. The repository serves as a resource hub for the initiative 'LLMs Meet Misinformation' and welcomes contributions of relevant research papers and resources. The goal is to facilitate interdisciplinary efforts in combating LLM-generated misinformation and promoting the responsible use of LLMs in fighting misinformation.

Awesome-LLM-Eval: a curated list of tools, benchmarks, demos, papers for Large Language Models (like ChatGPT, LLaMA, GLM, Baichuan, etc) Evaluation on Language capabilities, Knowledge, Reasoning, Fairness and Safety.

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.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

Awesome-Jailbreak-on-LLMs is a collection of state-of-the-art, novel, and exciting jailbreak methods on Large Language Models (LLMs). The repository contains papers, codes, datasets, evaluations, and analyses related to jailbreak attacks on LLMs. It serves as a comprehensive resource for researchers and practitioners interested in exploring various jailbreak techniques and defenses in the context of LLMs. Contributions such as additional jailbreak-related content, pull requests, and issue reports are welcome, and contributors are acknowledged. For any inquiries or issues, contact [email protected]. If you find this repository useful for your research or work, consider starring it to show appreciation.

A comprehensive repository focusing on 'Model Merging in LLMs, MLLMs, and Beyond', providing an exhaustive overview of model merging methods, theories, applications, and future research directions. The repository covers various advanced methods, applications in foundation models, different machine learning subfields, and tasks like pre-merging methods, architecture transformation, weight alignment, basic merging methods, and more.

Do-Not-Answer is an open-source dataset curated to evaluate Large Language Models' safety mechanisms at a low cost. It consists of prompts to which responsible language models do not answer. The dataset includes human annotations and model-based evaluation using a fine-tuned BERT-like evaluator. The dataset covers 61 specific harms and collects 939 instructions across five risk areas and 12 harm types. Response assessment is done for six models, categorizing responses into harmfulness and action categories. Both human and automatic evaluations show the safety of models across different risk areas. The dataset also includes a Chinese version with 1,014 questions for evaluating Chinese LLMs' risk perception and sensitivity to specific words and phrases.

This repository serves as a practical guide for Medical Large Language Models (Medical LLMs) and provides resources, surveys, and tools for building, fine-tuning, and utilizing LLMs in the medical domain. It covers a wide range of topics including pre-training, fine-tuning, downstream biomedical tasks, clinical applications, challenges, future directions, and more. The repository aims to provide insights into the opportunities and challenges of LLMs in medicine and serve as a practical resource for constructing effective medical LLMs.

SLMs-Survey is a comprehensive repository that includes papers and surveys on small language models. It covers topics such as technology, on-device applications, efficiency, enhancements for LLMs, and trustworthiness. The repository provides a detailed overview of existing SLMs, their architecture, enhancements, and specific applications in various domains. It also includes information on SLM deployment optimization techniques and the synergy between SLMs and LLMs.

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.

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.

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.

ABigSurveyOfLLMs is a repository that compiles surveys on Large Language Models (LLMs) to provide a comprehensive overview of the field. It includes surveys on various aspects of LLMs such as transformers, alignment, prompt learning, data management, evaluation, societal issues, safety, misinformation, attributes of LLMs, efficient LLMs, learning methods for LLMs, multimodal LLMs, knowledge-based LLMs, extension of LLMs, LLMs applications, and more. The repository aims to help individuals quickly understand the advancements and challenges in the field of LLMs through a collection of recent surveys and research papers.

Awesome LLM Courses is a curated list of online courses focused on Large Language Models (LLMs). The repository aims to provide a comprehensive collection of free available courses covering various aspects of LLMs, including fundamentals, engineering, and applications. The courses are suitable for individuals interested in natural language processing, AI development, and machine learning. The list includes courses from reputable platforms such as Hugging Face, Udacity, DeepLearning.AI, Cohere, DataCamp, and more, offering a wide range of topics from pretraining LLMs to building AI applications with LLMs. Whether you are a beginner looking to understand the basics of LLMs or an intermediate developer interested in advanced topics like prompt engineering and generative AI, this repository has something for everyone.

Download and Run Open Source LLMs Locally.

I explain AI papers in Chinese.

Specializes in summarizing LLM news and papers from the past week.

A guide for ML & LLM bootcamp with a bioengineering background.

General Information Gatherer

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

Your AI research aide for the latest in ML.

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Spot emerging trends in the latest social science research ( (also see, just "Research Radar" for all disciplines))

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Find and summarize recent papers in biology, chemistry, and biomedical sciences.

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