Best AI tools for< Conduct Multi-hop Reasoning >

Connex AI is an advanced AI platform offering a wide range of AI solutions for businesses across various industries. The platform provides cutting-edge features such as AI Agent, AI Guru, AI Voice, AI Analytics, Real-Time Coaching, Automated Speech Recognition, Sentiment Analysis, Keyphrase Analysis, Entity Recognition, LLM Topic-Based Modelling, SMS Live Chat, WhatsApp Voice, Email Dialler, PCI DSS, Social Media Flow, Calendar Schedular, Staff Management, Gamify Shop, PDF Builder, Pricing Matrix, Themes, Article Builder, Marketplace Integrations, and more. Connex AI aims to enhance customer engagement, workforce productivity, sales, and customer satisfaction through its innovative AI-driven solutions.

Synthetic Users is an AI-powered user research tool that allows users to conduct user and market research without the need for recruitment. The tool leverages advanced AI architecture to create human-like AI participants for in-depth interviews and surveys. By simulating real human interactions, Synthetic Users provides valuable insights for various applications, helping users optimize user journeys, prioritize product roadmaps, and enhance product discovery. The tool offers a multi-agent framework, proprietary data integration, and continuous learning capabilities to ensure relevant and reflective data outputs.

Norfolk AI is an AI application that offers AI agents to assist in B2B sales prospecting. The AI agents handle tasks like building databases, initiating outreach, qualifying leads, and organizing meetings via calls and chats. By leveraging advanced AI and proven sales techniques, Norfolk AI aims to create an efficient sales funnel, delivering qualified sales meetings that boost revenue and growth. The application combines AI technology with conversational AI for cold calling and multi-channel outreach to engage with interested prospects and generate high-quality sales opportunities.

The Berkeley Artificial Intelligence Research (BAIR) Lab is a renowned research lab at UC Berkeley focusing on computer vision, machine learning, natural language processing, planning, control, and robotics. With over 50 faculty members and 300 graduate students, BAIR conducts research on fundamental advances in AI and interdisciplinary themes like multi-modal deep learning and human-compatible AI.

Revmore is an AI-based revenue optimization platform that helps app and game developers grow their in-app purchase (IAP) and in-app advertising (IAA) revenue through AI-driven optimizations and improvements. The platform offers diverse optimization solutions, including customized package offerings, ad interval AB tests, and SKU price optimization. Revmore also provides effortless infrastructure integration with its multi-platform SDK, allowing seamless integration into existing tech stacks. The platform has received positive feedback from partners, showcasing significant increases in ad revenue, average revenue growth, and ARPPU. With Revmore, users can embark on an AI-powered revenue journey, leveraging automation, analytics, and seamless integration to elevate their revenue.

Workhub.ai is a website that offers a platform for conducting robot challenge screen tests. Users can assess the security of their site connection through this tool. The site prompts users to enable cookies in their browser settings to access the page.

SanptoBook is a personal accounting software designed to help individuals manage their finances efficiently. It offers features such as invoice and receipt management, reimbursement facilitation, tax filing assistance, bill splitting, and project tracking. The application aims to simplify financial tasks and improve overall financial organization for users. With AI-powered efficiency, SnaptoBook provides state-of-the-art receipt recognition technology and secure cloud storage for all receipts.

Poll the People is an AI-powered consumer research platform that offers 10X more effective surveys powered by ChatGPT. With a human panel of 500,000+ participants, the platform provides insights on brand testing, concept testing, logo testing, content testing, and more. By leveraging AI technology, users can make data-driven decisions, achieve faster insights, and access deep consumer understanding for better decision-making. The platform automates survey analysis, saving time and resources, and offers unbiased and accurate market insights. Poll the People is trusted by top brands worldwide for its efficiency and reliability in consumer research.

Rimo is a human-centered AI writer that helps you create high-quality content, fast. With Rimo, you can write blog posts, articles, website copy, social media posts, and more, in just a few minutes. Rimo's AI is trained on a massive dataset of human-written text, so it can generate content that is both informative and engaging.

The Website Audit AI is an AI-powered tool that offers free website audits and analysis for conversion rate optimization (CRO) and user experience (UX). It provides detailed insights and actionable recommendations to improve user experience and enhance conversion rates. The tool generates real reports based on data from actual users on genuine websites. With a focus on providing accurate and reliable information, Website Audit AI aims to help businesses optimize their online presence and drive better results.

Parroview is a revolutionary AI-powered user research platform that automates the process of conducting user interviews. It uses natural language processing (NLP) to engage with users in real-time conversations, asking follow-up questions and uncovering insights that would be difficult to obtain through traditional methods. Parroview is designed to be fully autonomous, allowing researchers to set up interviews and gather insights without the need for manual intervention. It supports multiple languages, making it accessible to a global audience. Parroview offers a range of features, including the ability to conduct interviews via text or voice, analyze insights in real-time, and generate detailed transcripts. It is suitable for a wide range of research needs, including product validation, consumer behavior analysis, post-purchase evaluations, brand perception studies, and customer persona development.

Wix.com is a website building platform that allows users to create stunning websites with ease. It offers a user-friendly interface with drag-and-drop functionality, making it simple for individuals and businesses to design their online presence. With a wide range of templates and customization options, Wix.com caters to users of all skill levels. Whether you're a beginner looking to build a personal blog or a professional wanting to showcase your portfolio, Wix.com provides the tools and features to bring your vision to life.

Recroo is a fully automated AI interview application that allows users to conduct interviews using artificial intelligence technology. The app is designed to streamline the screening process for recruiters by providing a real-interview like environment, complete feedback with ratings, AI assistant for answering questions, interview transcript review, and interview audio playback. Recroo simplifies the interview process by allowing users to provide job details and custom questions, while the AI engine takes care of conducting the interview. It is a powerful tool for recruiters looking to efficiently screen candidates and focus on other tasks.

EmpathixAI is an innovative AI tool designed to analyze and interpret human emotions through text and voice inputs. The tool uses advanced natural language processing and sentiment analysis algorithms to provide accurate insights into the emotional state of individuals. EmpathixAI helps businesses understand customer feedback, improve communication strategies, and enhance user experiences. With its user-friendly interface and powerful analytics capabilities, EmpathixAI is a valuable tool for companies looking to gain a deeper understanding of customer sentiment and emotions.

SciSpace is an AI-powered tool that helps researchers understand research papers better. It can explain and elaborate most academic texts in simple words. It is a great tool for students, researchers, and anyone who wants to learn more about a particular topic. SciSpace has a user-friendly interface and is easy to use. Simply upload a research paper or enter a URL, and SciSpace will do the rest. It will highlight key concepts, provide definitions, and generate a summary of the paper. SciSpace can also be used to generate citations and find related papers.

Search&AI is a comprehensive platform designed for patent due diligence, offering efficient and accurate results in minutes. It provides services such as prior art search, claim chart generation, novelty diligence analysis, portfolio analysis, document search, and AI-powered chatbot assistance. The platform is built by a team of experienced engineers and is tailored to streamline the patent discovery and analysis process, saving time and money compared to traditional outsourced search firms.

Ziggy is an AI-powered platform that automates 1-on-1 conversations, enabling users to conduct feedback interviews seamlessly with anyone, anytime. It helps businesses gather insightful and more natural responses from users than static forms ever could. Ziggy's commitment to collaboration and creativity helps teams work together to get the best results. Its powerful analytical tools help ensure users understand their users' wants and needs. With Ziggy, users can see the original responses from their users and use them to make better decisions.

Profundo is an AI-powered research assistant that automates data collection, analysis, and reporting. It enables users to conduct in-depth research on various topics efficiently and accurately. With cutting-edge AI algorithms, Profundo minimizes errors, maximizes productivity, and provides user-friendly interface for seamless integration with existing tools. Trusted by professionals, Profundo is used for self-study, content creation, academic research, industry analysis, and more.

Datarails is a financial planning and analysis platform for Excel users. It automates data consolidation, reporting, and planning while enabling finance teams to continue using their spreadsheets and financial models. With Datarails, finance teams can save time on repetitive tasks and focus on strategic insights that drive business growth.

InterviewAI is an AI-powered platform designed to streamline the interview process for both interviewers and candidates. It generates tailored interview questions in real-time, offers advanced practice tools, and provides automated scoring for candidate responses. The platform aims to enhance interview skills, boost confidence, and improve preparation for job seekers, companies, and educational institutions.

The GFM-RAG is a graph foundation model-powered pipeline that combines graph neural networks to reason over knowledge graphs and retrieve relevant documents for question answering. It features a knowledge graph index, efficiency in multi-hop reasoning, generalizability to unseen datasets, transferability for fine-tuning, compatibility with agent-based frameworks, and interpretability of reasoning paths. The tool can be used for conducting retrieval and question answering tasks using pre-trained models or fine-tuning on custom datasets.

This repository contains the source code and datasets for Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs accepted to ACL 2024. It proposes a framework called Graph Chain-of-thought (Graph-CoT) to enable Language Models to traverse graphs step-by-step for reasoning, interaction, and execution. The motivation is to alleviate hallucination issues in Language Models by augmenting them with structured knowledge sources represented as graphs.

This repository provides a curated list of papers, datasets, and resources related to the detection and mitigation of hallucinations in large language models (LLMs). Hallucinations refer to the generation of factually incorrect or nonsensical text by LLMs, which can be a significant challenge for their use in real-world applications. The resources in this repository aim to help researchers and practitioners better understand and address this issue.

The Eureka ML Insights Framework is a repository containing code designed to help researchers and practitioners run reproducible evaluations of generative models efficiently. Users can define custom pipelines for data processing, inference, and evaluation, as well as utilize pre-defined evaluation pipelines for key benchmarks. The framework provides a structured approach to conducting experiments and analyzing model performance across various tasks and modalities.

EasyEdit is a Python package for edit Large Language Models (LLM) like `GPT-J`, `Llama`, `GPT-NEO`, `GPT2`, `T5`(support models from **1B** to **65B**), the objective of which is to alter the behavior of LLMs efficiently within a specific domain without negatively impacting performance across other inputs. It is designed to be easy to use and easy to extend.

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.

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.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

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.

Search-R1 is a tool that trains large language models (LLMs) to reason and call a search engine using reinforcement learning. It is a reproduction of DeepSeek-R1 methods for training reasoning and searching interleaved LLMs, built upon veRL. Through rule-based outcome reward, the base LLM develops reasoning and search engine calling abilities independently. Users can train LLMs on their own datasets and search engines, with preliminary results showing improved performance in search engine calling and reasoning tasks.

GOLEM is an open-source AI framework focused on optimization and learning of structured graph-based models using meta-heuristic methods. It emphasizes the potential of meta-heuristics in complex problem spaces where gradient-based methods are not suitable, and the importance of structured models in various problem domains. The framework offers features like structured model optimization, metaheuristic methods, multi-objective optimization, constrained optimization, extensibility, interpretability, and reproducibility. It can be applied to optimization problems represented as directed graphs with defined fitness functions. GOLEM has applications in areas like AutoML, Bayesian network structure search, differential equation discovery, geometric design, and neural architecture search. The project structure includes packages for core functionalities, adapters, graph representation, optimizers, genetic algorithms, utilities, serialization, visualization, examples, and testing. Contributions are welcome, and the project is supported by ITMO University's Research Center Strong Artificial Intelligence in Industry.

Kuwa GenAI OS is an open, free, secure, and privacy-focused Generative-AI Operating System. It provides a multi-lingual turnkey solution for GenAI development and deployment on Linux and Windows. Users can enjoy features such as concurrent multi-chat, quoting, full prompt-list import/export/share, and flexible orchestration of prompts, RAGs, bots, models, and hardware/GPUs. The system supports various environments from virtual hosts to cloud, and it is open source, allowing developers to contribute and customize according to their needs.

The enhance_llm repository contains three main parts: 1. Vector model domain fine-tuning based on llama_index and qwen fine-tuning BGE vector model. 2. Large model domain fine-tuning based on PEFT fine-tuning qwen1.5-7b-chat, with sft and dpo. 3. High-order retrieval enhanced generation (RAG) system based on the above domain work, implementing a two-stage RAG system. It includes query rewriting, recall reordering, retrieval reordering, multi-turn dialogue, and more. The repository also provides hardware and environment configurations along with star history and licensing information.

LLM Reasoners is a library that enables LLMs to conduct complex reasoning, with advanced reasoning algorithms. It approaches multi-step reasoning as planning and searches for the optimal reasoning chain, which achieves the best balance of exploration vs exploitation with the idea of "World Model" and "Reward". Given any reasoning problem, simply define the reward function and an optional world model (explained below), and let LLM reasoners take care of the rest, including Reasoning Algorithms, Visualization, LLM calling, and more!

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

This repository provides code to deploy a chatbot powered by Multi-Model and Multi-RAG using AWS CDK on AWS. Users can experiment with various Large Language Models and Multimodal Language Models from different providers. The solution supports Amazon Bedrock, Amazon SageMaker self-hosted models, and third-party providers via API. It also offers additional resources like AWS Generative AI CDK Constructs and Project Lakechain for building generative AI solutions and document processing. The roadmap and authors are listed, along with contributors. The library is licensed under the MIT-0 License with information on changelog, code of conduct, and contributing guidelines. A legal disclaimer advises users to conduct their own assessment before using the content for production purposes.

The Together Cookbook is a collection of code and guides designed to help developers build with open source models using Together AI. The recipes provide examples on how to chain multiple LLM calls, create agents that route tasks to specialized models, run multiple LLMs in parallel, break down tasks into parallel subtasks, build agents that iteratively improve responses, perform LoRA fine-tuning and inference, fine-tune LLMs for repetition, improve summarization capabilities, fine-tune LLMs on multi-step conversations, implement retrieval-augmented generation, conduct multimodal search and conditional image generation, visualize vector embeddings, improve search results with rerankers, implement vector search with embedding models, extract structured text from images, summarize and evaluate outputs with LLMs, generate podcasts from PDF content, and get LLMs to generate knowledge graphs.

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