Python wrapper for evaluating summarization quality by ROUGE package

Document Search Engine Tool

Code for the paper "Efficient Adaption of Pretrained Transformers for Abstractive Summarization"

Extractive Document Summarization Based on Convolutional Neural Networks

A python application for summarizing Slack threads

[NAACL2018] Entity Commonsense Representation for Neural Abstractive Summarization

[ACL2020] Unsupervised Opinion Summarization with Noising and Denoising

Ally – AI Contract Assistant is a Word plugin using Azure OpenAI for contract analysis, real-time Q&A, and auto-markup. It helps legal professionals save time and ensure accuracy in reviews.

문서 요약 논문 정리

Implementation for multi-document query-based abstractive summarisation

LoRA supervised fine-tuning, RLHF (PPO) and RAG with llama-3-8B on the TLDR summarization dataset

Summarize documents based on content extracted via Rosette API

Automatic Extractive Text Summarization using TF-IDF Frequency Analysis. This is a Node.js web application using Express.js on the server side.

Simple Query Based Document Summarization

Extract Amazon customer reviews of select products via a third-party educational web scrapper, analyze them with LLM, and display concise summaries using an interactive user interface.

Muisca: Modelo Unificado de Inteligencia Supervisada para la Computación y Aplicación. Una herramienta Streamlit para resumir y hacer preguntas sobre documentos en PDF y TXT utilizando modelos de lenguaje de última generación.

Document summarisation and query expansion

agentnovax-api-rag-springboot-ollama-pgvector is a Spring Boot-based API that combines Retrieval-Augmented Generation (RAG) with the Ollama language model API and pgvector for vector search in PostgreSQL. It enables scalable, intelligent AI solutions for applications like recommendation systems, chatbots, and context-aware responses.

Document Summarization has become a vital task for various individuals and businesses that require a way of cutting down complexities involved with bulky documents

This project demonstrates summarizing large documents with Azure OpenAI and Durable Functions, using a Fan-out/Fan-in pattern to process sections in parallel and compile a cohesive summary. It ensures scalable and efficient document handling with Azure services.