Advanced RAG pipeline using Re-Ranking after initial retrieval
-
Updated
May 11, 2024 - Python
Advanced RAG pipeline using Re-Ranking after initial retrieval
This repository is dedicated to exploring and implementing vector-based retrieval methods and reranking algorithms. It includes Jupyter notebooks with practical examples and code snippets that demonstrate how these techniques can be applied for efficient information retrieval in various datasets.
predicting a movie list with Two-sided Fairness-aware Recommendation Model (accotding to TFROM_A article) dataset : https://grouplens.org/datasets/movielens/100k/
6th sem mini project
Exploring search relevance techniques.
Assignment on Information Retrieval course, implementing ranking algorithms with Lucene.
A Java implementation of the classical Information Retrieval models in the TREC-COVID Challenge with the CORD19 Dataset
Frontend for comic book semantic search engine. Renders explanations along with search results
Library for plotting multiple ranks evolved over processing steps - draw a rankflow/bump chart
Multi-stage Retrieval using SPLADE or RM3 and T5.
This repository showcases a comprehensive approach to information retrieval, document re-ranking, and language model integration. It incorporates techniques such as document chunking, embedding projection, and automatic query expansion to enhance the effectiveness of information retrieval systems.
Training a customized dataset on fast-reid, evaluation and visualization
Information Retrieval using KoSentence-BERT
임베딩(SentenceTransformer) 및 재순위화(Re-Ranking)
Smart Untact Meeting / 전문가추천시스템 APP
Implementation of Probabilistic Retrieval Query expansion and Relevance Model based Language Modelling aimed at improving the precision of results using pseudo-relevance feedback in Information Retrieval.
This is an official implementation for "Robust Graph Structure Learning over Images via Multiple Statistical Tests" accepted at NeurIPS 2022.
Add a description, image, and links to the reranking topic page so that developers can more easily learn about it.
To associate your repository with the reranking topic, visit your repo's landing page and select "manage topics."