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06/07/2023
RD-Suite: A Benchmark for Ranking Distillation
The distillation of ranking models has become an important topic in both...
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05/05/2023
Query Expansion by Prompting Large Language Models
Query expansion is a widely used technique to improve the recall of sear...
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11/02/2022
Regression Compatible Listwise Objectives for Calibrated Ranking
As Learning-to-Rank (LTR) approaches primarily seek to improve ranking q...
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10/12/2022
RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses
Recently, substantial progress has been made in text ranking based on pr...
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05/21/2020
Accelerated Convergence for Counterfactual Learning to Rank
Counterfactual Learning to Rank (LTR) algorithms learn a ranking model f...
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02/02/2020
Safe Exploration for Optimizing Contextual Bandits
Contextual bandit problems are a natural fit for many information retrie...
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07/16/2019
Unbiased Learning to Rank: Counterfactual and Online Approaches
This tutorial covers and contrasts the two main methodologies in unbiase...
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07/15/2019
To Model or to Intervene: A Comparison of Counterfactual and Online Learning to Rank from User Interactions
Learning to Rank (LTR) from user interactions is challenging as user fee...
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07/24/2017
Modeling Label Ambiguity for Neural List-Wise Learning to Rank
List-wise learning to rank methods are considered to be the state-of-the...
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05/24/2016
Computing Web-scale Topic Models using an Asynchronous Parameter Server
Topic models such as Latent Dirichlet Allocation (LDA) have been widely ...
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11/11/2015
