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01/08/2023
InPars-Light: Cost-Effective Unsupervised Training of Efficient Rankers
We carried out a reproducibility study of InPars recipe for unsupervised...
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07/04/2022
Understanding Performance of Long-Document Ranking Models through Comprehensive Evaluation and Leaderboarding
We carry out a comprehensive evaluation of 13 recent models for ranking ...
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05/12/2022
Smooth-Reduce: Leveraging Patches for Improved Certified Robustness
Randomized smoothing (RS) has been shown to be a fast, scalable techniqu...
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03/04/2021
A Systematic Evaluation of Transfer Learning and Pseudo-labeling with BERT-based Ranking Models
Due to high annotation costs, making the best use of existing human-crea...
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02/12/2021
Exploring Classic and Neural Lexical Translation Models for Information Retrieval: Interpretability, Effectiveness, and Efficiency Benefits
We study the utility of the lexical translation model (IBM Model 1) for ...
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12/15/2020
Traditional IR rivals neural models on the MSÂ MARCO Document Ranking Leaderboard
This short document describes a traditional IR system that achieved MRR@...
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10/28/2020
Flexible retrieval with NMSLIB and FlexNeuART
Our objective is to introduce to the NLP community an existing k-NN sear...
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12/20/2019
SberQuAD – Russian Reading Comprehension Dataset: Description and Analysis
SberQuAD—a large scale analog of Stanford SQuAD in the Russian language—...
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10/08/2019
Pruning Algorithms for Low-Dimensional Non-metric k-NN Search: A Case Study
We focus on low-dimensional non-metric search, where tree-based approach...
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10/08/2019
Accurate and Fast Retrieval for Complex Non-metric Data via Neighborhood Graphs
We demonstrate that a graph-based search algorithm-relying on the constr...
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11/08/2017
