Found 24 repositories(showing 24)
jonathanscholtes
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.
achrefbenammar404
Official implementation of the research paper: "Markov-Enhanced Clustering for Long Document Summarization: Tackling the 'Lost in the Middle' Challenge with Large Language Models" by Aziz Amari and Mohamed Achref Ben Ammar, INSAT, University of Carthage, Tunisia.
Elkhiat15
No description available
No description available
sudilate
Summarization of large files like (pdf, txt,doc) with Map Reduce technique with both generic and customised prompt.
hbcbh1999
No description available
nickwiecien
No description available
NayabAshraf
No description available
namtran6701
No description available
sumukshashidhar-archive
Summarizing large documents (beyond token limits) with a Large Language Model, using a reflection based architecture
Dinidu-Lochana
No description available
demekeendalie
No description available
No description available
This assignment is about building a Document Search + Summarization system using a Large Language Model (LLM) such as GPT-4 or similar.
A scalable NLP system that combines traditional information retrieval and LLM embeddings to search large document corpora and generate concise, high-quality summaries.
The main objective of his assignment is to design a system that can search and summarize vast amounts of textual data efficiently.
No description available
Offline Retrieval-Augmented Generation system for local documents: hybrid retrieval (BM25 + FAISS), chunking + indexing, and grounded answers/summaries generated via a locally hosted LLaMA model-no external APIs required.
No description available
SZU-AdvTech-2024-Test
No description available
PrernaKumari1990
Text Summarization is the creation of short, accurate summaries from longer document. Here I have used a NLP model named "Pegasus" because it is a pretrained model on large corpus of diverse text data and then fine tuned for specific summarization tasks. It is a abstractive text summarization, means it can generate a concise summary of given doc.
NickNiu0530
This tool now supports automatically extracting subtitles via video links, integrating with large language models to achieve text summarization, translation, and professional term tagging, and synchronizing the processed results to Feishu Docs with a single click.
jatinkanyan
Summarization Engine using Google Gemini API and LangChain. Converts long clinical or compliance documents like discharge notes or transcripts into concise, multi-paragraph summaries using MapReduce or Refine chains, with support for PDF/text input and chunking for large docs.
A-keerthana
A Fine-tuned BART for legal document summarization, 88% roughly scored 🧠 Hugging Face Transformers (BART-large-cnn) fine-tuned on legal datasets 🚀 Streamlit web app for easy testing & Dockerized for production deployment ⚖️ Preserves key clauses while reducing doc length by 70% 🔍 Customizable for different legal domains (corporate, IP, etc.)
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