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05/19/2023
Exploring the Viability of Synthetic Query Generation for Relevance Prediction
Query-document relevance prediction is a critical problem in Information...
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12/19/2022
DSI++: Updating Transformer Memory with New Documents
Differentiable Search Indices (DSIs) encode a corpus of documents in the...
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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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01/25/2022
Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models
The pre-trained language model (eg, BERT) based deep retrieval models ac...
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01/07/2022
Data-Efficient Information Extraction from Form-Like Documents
Automating information extraction from form-like documents at scale is a...
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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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06/11/2021
Dynamic Language Models for Continuously Evolving Content
The content on the web is in a constant state of flux. New entities, iss...
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05/05/2021
Rethinking Search: Making Experts out of Dilettantes
When experiencing an information need, users want to engage with an expe...
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04/15/2021
Privacy-Adaptive BERT for Natural Language Understanding
When trying to apply the recent advance of Natural Language Understandin...
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03/02/2021
WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning
The milestone improvements brought about by deep representation learning...
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10/22/2020
Scalable Bottom-Up Hierarchical Clustering
Bottom-up algorithms such as the classic hierarchical agglomerative clus...
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10/07/2020
DiPair: Fast and Accurate Distillation for Trillion-Scale Text Matching and Pair Modeling
Pre-trained models like BERT (Devlin et al., 2018) have dominated NLP / ...
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10/02/2020
Leveraging Semantic and Lexical Matching to Improve the Recall of Document Retrieval Systems: A Hybrid Approach
Search engines often follow a two-phase paradigm where in the first stag...
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05/23/2020
Active Learning for Skewed Data Sets
Consider a sequential active learning problem where, at each round, an a...
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04/26/2020
Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Document Matching
Many information retrieval and natural language processing problems can ...
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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