There are 3 repositories under reranking topic.
MTEB: Massive Text Embedding Benchmark
A curated list of awesome papers related to pre-trained models for information retrieval (a.k.a., pretraining for IR).
[EMNLP 2023 Outstanding Paper Award] Is ChatGPT Good at Search? LLMs as Re-Ranking Agent
Querying local documents, powered by LLM
Ultra-lite & Super-fast re-ranking for your search & retrieval pipelines. Based on SoTA models like cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.
Diffusion on manifolds for image retrieval
Code, datasets, and checkpoints for the paper "Improving Passage Retrieval with Zero-Shot Question Generation (EMNLP 2022)"
Code and resources for papers "Generation-Augmented Retrieval for Open-Domain Question Answering" and "Reader-Guided Passage Reranking for Open-Domain Question Answering", ACL 2021
Bag of Visual Feature with Hamming Enbedding, Reranking
Energy-based modeling of chemical reactions
[ACL 2023] Few-shot Reranking for Multi-hop QA via Language Model Prompting
Simple script to re-rank images using OpenAI's CLIP https://github.com/openai/CLIP.
Improving Bilingual Lexicon Induction with Cross-Encoder Reranking (Findings of EMNLP 2022). Keywords: Bilingual Lexicon Induction, Word Translation, Cross-Lingual Word Embeddings.
Explore from keyword search to dense retrieval and reranking, which injects the intelligence of LLMs into your search system, making it faster and more effective.
Wikipedia Semantic Search w/ Embeddings
Python-based toolkit for building and evaluating a transformer-based FAQ retrieval system
Who's that Pokemon (card)? Search over more than 10K Pokemon cards to find out the coolest one yet! ✨
This is an official implementation for "Robust Graph Structure Learning over Images via Multiple Statistical Tests" accepted at NeurIPS 2022.
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.
Smart Untact Meeting / 전문가추천시스템 APP
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.
Alpaca, Bloom, DeciLM, Falcon, Vicuna, Llama2, Zephyr, Mistral(MoE), RAG, Reranking, Langchain, Langsmith..
Information Retrieval using KoSentence-BERT
Multi-stage Retrieval using SPLADE or RM3 and T5.
임베딩(SentenceTransformer) 및 재순위화(Re-Ranking)
Frontend for comic book semantic search engine. Renders explanations along with search results
Training a customized dataset on fast-reid, evaluation and visualization
A Java implementation of the classical Information Retrieval models in the TREC-COVID Challenge with the CORD19 Dataset
Exploring search relevance techniques.
predicting a movie list with Two-sided Fairness-aware Recommendation Model (accotding to TFROM_A article) dataset : https://grouplens.org/datasets/movielens/100k/