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06/14/2023
Learning to Rank when Grades Matter
Graded labels are ubiquitous in real-world learning-to-rank applications...
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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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06/05/2023
LibAUC: A Deep Learning Library for X-Risk Optimization
This paper introduces the award-winning deep learning (DL) library calle...
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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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04/17/2023
Metric-agnostic Ranking Optimization
Ranking is at the core of Information Retrieval. Classic ranking optim...
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12/21/2022
Learning List-Level Domain-Invariant Representations for Ranking
Domain adaptation aims to transfer the knowledge acquired by models trai...
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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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12/17/2021
Rank4Class: A Ranking Formulation for Multiclass Classification
Multiclass classification (MCC) is a fundamental machine learning proble...
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09/30/2021
Born Again Neural Rankers
We introduce Born Again neural Rankers (BAR) in the Learning to Rank (LT...
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01/21/2021
Distilling Interpretable Models into Human-Readable Code
The goal of model distillation is to faithfully transfer teacher model k...
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05/18/2020
Unbiased Learning to Rank via Propensity Ratio Scoring
Implicit feedback, such as user clicks, is a major source of supervision...
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05/06/2020
Interpretable Learning-to-Rank with Generalized Additive Models
Interpretability of learning-to-rank models is a crucial yet relatively ...
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04/17/2020
Learning-to-Rank with BERT in TF-Ranking
This paper describes a machine learning algorithm for document (re)ranki...
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10/21/2019
Self-Attentive Document Interaction Networks for Permutation Equivariant Ranking
How to leverage cross-document interactions to improve ranking performan...
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12/12/2018
Estimating Position Bias without Intrusive Interventions
Presentation bias is one of the key challenges when learning from implic...
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11/30/2018
TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank
TensorFlow Ranking is the first open source library for solving large-sc...
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11/11/2018
Learning Groupwise Scoring Functions Using Deep Neural Networks
While in a classification or a regression setting a label or a value is ...
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10/11/2018
Offline Comparison of Ranking Functions using Randomized Data
Ranking functions return ranked lists of items, and users often interact...
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03/31/2010