Query Expension for Better Query Embedding using LLMs
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Updated
Feb 18, 2025 - Python
Query Expension for Better Query Embedding using LLMs
Code and resources for the paper "BERT-QE: Contextualized Query Expansion for Document Re-ranking".
Code for the ACL 2023 long paper - Expand, Rerank, and Retrieve: Query Reranking for Open-Domain Question Answering
SIGIR 2017: Embedding-based query expansion for weighted sequential dependence retrieval model
A Benchmark Workflow and Dataset Collection for Query Refinement
CS 582 Information Retrieval at University of Illinois at Chicago. Multithreaded crawling of UIC domain, inverted index, page rank, SEO with Context Pseudo-Relevance Feedback
Implementation query expansion in semantic meta-search engine. The resulting expansion system is called Wiki-MetaSemantik.
Query Expansion via thesaurus
A search engine built to retrieve geographical information of any country.
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.
SIR is a sense-enhanced Information Retrieval system for multiple languages (EMNLP2021).
A basic search engine to index a corpus for searching and rank the document data set.
Search engine specifically targeted to Olympics
LLM-based Listwise Reranker for Retrieval-Augmented Generation (RAG) over GitHub code repositories. Includes advanced retrieval, reranking, summarization, and evaluation with Recall@K.
Document summarisation and query expansion
Naver AI Hackathon 2018 : Image Retrieval Challenge
TTDS 2022/23. Course page: https://www.inf.ed.ac.uk/teaching/courses/tts/
A python program for indexing documents and querying them with expansion over Elasticsearch engine
Multi-stage Retrieval using SPLADE or RM3 and T5.
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