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09/19/2023
Large language models can accurately predict searcher preferences
Relevance labels, which indicate whether a search result is valuable to ...
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04/25/2023
Patterns of gender-specializing query reformulation
Users of search systems often reformulate their queries by adding query ...
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02/22/2023
Recall as a Measure of Ranking Robustness
Researchers use recall to evaluate rankings across a variety of retrieva...
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01/12/2023
Taking Search to Task
The importance of tasks in information retrieval (IR) has been long argu...
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09/08/2022
Ethical and Social Considerations in Automatic Expert Identification and People Recommendation in Organizational Knowledge Management Systems
Organizational knowledge bases are moving from passive archives to activ...
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06/26/2022
Are We There Yet? A Decision Framework for Replacing Term Based Retrieval with Dense Retrieval Systems
Recently, several dense retrieval (DR) models have demonstrated competit...
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04/29/2022
Joint Multisided Exposure Fairness for Recommendation
Prior research on exposure fairness in the context of recommender system...
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01/21/2022
Less is Less: When Are Snippets Insufficient for Human vs Machine Relevance Estimation?
Traditional information retrieval (IR) ranking models process the full t...
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10/15/2021
Revisiting Popularity and Demographic Biases in Recommender Evaluation and Effectiveness
Recommendation algorithms are susceptible to popularity bias: a tendency...
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10/14/2021
Exposing Query Identification for Search Transparency
Search systems control the exposure of ranked content to searchers. In m...
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05/20/2021
Intra-Document Cascading: Learning to Select Passages for Neural Document Ranking
An emerging recipe for achieving state-of-the-art effectiveness in neura...
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05/10/2021
Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models
In any ranking system, the retrieval model outputs a single score for a ...
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05/09/2021
MS MARCO: Benchmarking Ranking Models in the Large-Data Regime
Evaluation efforts such as TREC, CLEF, NTCIR and FIRE, alongside public ...
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05/06/2021
Multi-FR: A Multi-Objective Optimization Method for Achieving Two-sided Fairness in E-commerce Recommendation
Two-sided marketplaces are an important component of many existing Inter...
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04/19/2021
TREC Deep Learning Track: Reusable Test Collections in the Large Data Regime
The TREC Deep Learning (DL) Track studies ad hoc search in the large dat...
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04/19/2021
Improving Transformer-Kernel Ranking Model Using Conformer and Query Term Independence
The Transformer-Kernel (TK) model has demonstrated strong reranking perf...
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02/25/2021
Significant Improvements over the State of the Art? A Case Study of the MS MARCO Document Ranking Leaderboard
Leaderboards are a ubiquitous part of modern research in applied machine...
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02/15/2021
Overview of the TREC 2020 deep learning track
This is the second year of the TREC Deep Learning Track, with the goal o...
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01/18/2021
Tip of the Tongue Known-Item Retrieval: A Case Study in Movie Identification
While current information retrieval systems are effective for known-item...
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12/21/2020
Neural Methods for Effective, Efficient, and Exposure-Aware Information Retrieval
Neural networks with deep architectures have demonstrated significant pe...
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11/14/2020
Conformer-Kernel with Query Term Independence at TREC 2020 Deep Learning Track
We benchmark Conformer-Kernel models under the strict blind evaluation s...
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08/18/2020
Semantic Product Search for Matching Structured Product Catalogs in E-Commerce
Retrieving all semantically relevant products from the product catalog i...
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07/20/2020
Conformer-Kernel with Query Term Independence for Document Retrieval
The Transformer-Kernel (TK) model has demonstrated strong reranking perf...
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06/09/2020
ORCAS: 18 Million Clicked Query-Document Pairs for Analyzing Search
Users of Web search engines reveal their information needs through queri...
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05/30/2020
Analyzing and Learning from User Interactions for Search Clarification
Asking clarifying questions in response to search queries has been recog...
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05/11/2020
Local Self-Attention over Long Text for Efficient Document Retrieval
Neural networks, particularly Transformer-based architectures, have achi...
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04/28/2020
On the Reliability of Test Collections for Evaluating Systems of Different Types
As deep learning based models are increasingly being used for informatio...
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04/27/2020
Evaluating Stochastic Rankings with Expected Exposure
We introduce the concept of expected exposure as the average attention r...
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03/17/2020
Overview of the TREC 2019 deep learning track
The Deep Learning Track is a new track for TREC 2019, with the goal of s...
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12/20/2019
Report on the First HIPstIR Workshop on the Future of Information Retrieval
The vision of HIPstIR is that early stage information retrieval (IR) res...
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12/10/2019
Duet at TREC 2019 Deep Learning Track
This report discusses three submissions based on the Duet architecture t...
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07/08/2019
Incorporating Query Term Independence Assumption for Efficient Retrieval and Ranking using Deep Neural Networks
Classical information retrieval (IR) methods, such as query likelihood a...
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04/15/2019
An Axiomatic Approach to Regularizing Neural Ranking Models
Axiomatic information retrieval (IR) seeks a set of principle properties...
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03/18/2019
An Updated Duet Model for Passage Re-ranking
We propose several small modifications to Duet---a deep neural ranking m...
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07/21/2018
A Line in the Sand: Recommendation or Ad-hoc Retrieval?
The popular approaches to recommendation and ad-hoc retrieval tasks are ...
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05/09/2018
Cross Domain Regularization for Neural Ranking Models Using Adversarial Learning
Unlike traditional learning to rank models that depend on hand-crafted f...
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04/12/2018
Optimizing Query Evaluations using Reinforcement Learning for Web Search
In web search, typically a candidate generation step selects a small set...
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11/25/2017
Neural Ranking Models with Multiple Document Fields
Deep neural networks have recently shown promise in the ad-hoc retrieval...
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10/17/2017
Reply With: Proactive Recommendation of Email Attachments
Email responses often contain items-such as a file or a hyperlink to an ...
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07/20/2017
Toward Incorporation of Relevant Documents in word2vec
Recent advances in neural word embedding provide significant benefit to ...
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07/13/2017
Neural Networks for Information Retrieval
Machine learning plays a role in many aspects of modern IR systems, and ...
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05/25/2016