Information Retrieval
841 papers with code • 10 benchmarks • 82 datasets
Information retrieval is the task of ranking a list of documents or search results in response to a query
( Image credit: sudhanshumittal )
Benchmarks
These leaderboards are used to track progress in Information Retrieval
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Libraries
Use these libraries to find Information Retrieval models and implementations
MS MARCO
BioASQ
CORD-19
PubLayNet
QASC
MTEB
MedleyDB
Subtasks
Most implemented papers
Unsupervised Dense Information Retrieval with Contrastive Learning
facebookresearch/contriever
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In this work, we explore the limits of contrastive learning as a way to train unsupervised dense retrievers and show that it leads to strong performance in various retrieval settings.
Active learning in annotating micro-blogs dealing with e-reputation
This paper intends to develop a so-called active learning process for automatically annotating French language tweets that deal with the image (i. e., representation, web reputation) of politicians.
Music Artist Classification with Convolutional Recurrent Neural Networks
ZainNasrullah/music-artist-classification-crnn
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To this end, an established classification architecture, a Convolutional Recurrent Neural Network (CRNN), is applied to the artist20 music artist identification dataset under a comprehensive set of conditions.
Multi-Interest Network with Dynamic Routing for Recommendation at Tmall
Industrial recommender systems usually consist of the matching stage and the ranking stage, in order to handle the billion-scale of users and items.
Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance
jingtaozhan/JPQ
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Compared with previous DR models that use brute-force search, JPQ almost matches the best retrieval performance with 30x compression on index size.
Infinite Recommendation Networks: A Data-Centric Approach
We leverage the Neural Tangent Kernel and its equivalence to training infinitely-wide neural networks to devise $\infty$-AE: an autoencoder with infinitely-wide bottleneck layers.
SCDV : Sparse Composite Document Vectors using soft clustering over distributional representations
We present a feature vector formation technique for documents - Sparse Composite Document Vector (SCDV) - which overcomes several shortcomings of the current distributional paragraph vector representations that are widely used for text representation.
Neural Vector Spaces for Unsupervised Information Retrieval
We propose the Neural Vector Space Model (NVSM), a method that learns representations of documents in an unsupervised manner for news article retrieval.
Revisiting Singing Voice Detection: a Quantitative Review and the Future Outlook
Since the vocal component plays a crucial role in popular music, singing voice detection has been an active research topic in music information retrieval.
