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09/18/2023
Predictive Uncertainty-based Bias Mitigation in Ranking
Societal biases that are contained in retrieved documents have received ...
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08/29/2023
Continual Learning for Generative Retrieval over Dynamic Corpora
Generative retrieval (GR) directly predicts the identifiers of relevant ...
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08/19/2023
Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method
Neural ranking models (NRMs) and dense retrieval (DR) models have given ...
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08/05/2023
Group Membership Bias
When learning to rank from user interactions, search and recommendation ...
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08/02/2023
Masked and Swapped Sequence Modeling for Next Novel Basket Recommendation in Grocery Shopping
Next basket recommendation (NBR) is the task of predicting the next set ...
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07/08/2023
Answering Ambiguous Questions via Iterative Prompting
In open-domain question answering, due to the ambiguity of questions, mu...
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06/15/2023
RecFusion: A Binomial Diffusion Process for 1D Data for Recommendation
In this paper we propose RecFusion, which comprise a set of diffusion mo...
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05/26/2023
Distributional Reinforcement Learning with Dual Expectile-Quantile Regression
Successful applications of distributional reinforcement learning with qu...
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05/22/2023
MultiTabQA: Generating Tabular Answers for Multi-Table Question Answering
Recent advances in tabular question answering (QA) with large language m...
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05/18/2023
Query Performance Prediction: From Ad-hoc to Conversational Search
Query performance prediction (QPP) is a core task in information retriev...
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05/17/2023
Iteratively Learning Representations for Unseen Entities with Inter-Rule Correlations
Recent work on knowledge graph completion (KGC) focused on learning embe...
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05/09/2023
Improving Implicit Feedback-Based Recommendation through Multi-Behavior Alignment
Recommender systems that learn from implicit feedback often use large vo...
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05/01/2023
On the Impact of Outlier Bias on User Clicks
User interaction data is an important source of supervision in counterfa...
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04/28/2023
Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models
Neural ranking models (NRMs) have attracted considerable attention in in...
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04/28/2023
A Unified Generative Retriever for Knowledge-Intensive Language Tasks via Prompt Learning
Knowledge-intensive language tasks (KILTs) benefit from retrieving high-...
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04/26/2023
Safe Deployment for Counterfactual Learning to Rank with Exposure-Based Risk Minimization
Counterfactual learning to rank (CLTR) relies on exposure-based inverse ...
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04/19/2023
An Offline Metric for the Debiasedness of Click Models
A well-known problem when learning from user clicks are inherent biases ...
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04/09/2023
Learning to Tokenize for Generative Retrieval
Conventional document retrieval techniques are mainly based on the index...
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03/04/2023
A Self-Correcting Sequential Recommender
Sequential recommendations aim to capture users' preferences from their ...
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01/20/2023
Generative Slate Recommendation with Reinforcement Learning
Recent research has employed reinforcement learning (RL) algorithms to o...
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01/12/2023
Scene-centric vs. Object-centric Image-Text Cross-modal Retrieval: A Reproducibility Study
Most approaches to cross-modal retrieval (CMR) focus either on object-ce...
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01/04/2023
Modeling Sequential Recommendation as Missing Information Imputation
Side information is being used extensively to improve the effectiveness ...
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01/03/2023
Offline Evaluation for Reinforcement Learning-based Recommendation: A Critical Issue and Some Alternatives
In this paper, we argue that the paradigm commonly adopted for offline e...
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12/20/2022
Contrastive Learning Reduces Hallucination in Conversations
Pre-trained language models (LMs) store knowledge in their parameters an...
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12/11/2022
Feature-Level Debiased Natural Language Understanding
Natural language understanding (NLU) models often rely on dataset biases...
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09/17/2022
RADio – Rank-Aware Divergence Metrics to Measure Normative Diversity in News Recommendations
In traditional recommender system literature, diversity is often seen as...
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09/14/2022
Certified Robustness to Word Substitution Ranking Attack for Neural Ranking Models
Neural ranking models (NRMs) have achieved promising results in informat...
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08/19/2022
Intersection of Parallels as an Early Stopping Criterion
A common way to avoid overfitting in supervised learning is early stoppi...
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07/06/2022
Towards the Use of Saliency Maps for Explaining Low-Quality Electrocardiograms to End Users
When using medical images for diagnosis, either by clinicians or artific...
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06/24/2022
Debiasing Learning for Membership Inference Attacks Against Recommender Systems
Learned recommender systems may inadvertently leak information about the...
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05/30/2022
GLDQN: Explicitly Parameterized Quantile Reinforcement Learning for Waste Reduction
We study the problem of restocking a grocery store's inventory with peri...
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05/25/2022
Fairness of Exposure in Light of Incomplete Exposure Estimation
Fairness of exposure is a commonly used notion of fairness for ranking s...
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05/10/2022
State Encoders in Reinforcement Learning for Recommendation: A Reproducibility Study
Methods for reinforcement learning for recommendation (RL4Rec) are incre...
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05/05/2022
A Simple Contrastive Learning Objective for Alleviating Neural Text Degeneration
The cross-entropy objective has proved to be an all-purpose training obj...
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04/28/2022
Probabilistic Permutation Graph Search: Black-Box Optimization for Fairness in Ranking
There are several measures for fairness in ranking, based on different u...
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04/28/2022
Keep the Caption Information: Preventing Shortcut Learning in Contrastive Image-Caption Retrieval
To train image-caption retrieval (ICR) methods, contrastive loss functio...
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04/26/2022
Understanding User Satisfaction with Task-oriented Dialogue Systems
Dialogue systems are evaluated depending on their type and purpose. Two ...
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04/15/2022
Summarization with Graphical Elements
Automatic text summarization has experienced substantial progress in rec...
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04/07/2022
Parameter-Efficient Abstractive Question Answering over Tables or Text
A long-term ambition of information seeking QA systems is to reason over...
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04/02/2022
Metaphorical User Simulators for Evaluating Task-oriented Dialogue Systems
Task-oriented dialogue systems (TDSs) are assessed mainly in an offline ...
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02/14/2022
Do Lessons from Metric Learning Generalize to Image-Caption Retrieval?
The triplet loss with semi-hard negatives has become the de facto choice...
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12/21/2021
Extending CLIP for Category-to-image Retrieval in E-commerce
E-commerce provides rich multimodal data that is barely leveraged in pra...
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12/21/2021
Understanding and Mitigating the Effect of Outliers in Fair Ranking
Traditional ranking systems are expected to sort items in the order of t...
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11/24/2021
It Is Different When Items Are Older: Debiasing Recommendations When Selection Bias and User Preferences Are Dynamic
User interactions with recommender systems (RSs) are affected by user se...
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11/01/2021
Teaching Fairness, Accountability, Confidentiality, and Transparency in Artificial Intelligence through the Lens of Reproducibility
In this work we explain the setup for a technical, graduate-level course...
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09/29/2021
A Next Basket Recommendation Reality Check
The goal of a next basket recommendation (NBR) system is to recommend it...
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08/24/2021
sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel Classification
Multiclass multilabel classification refers to the task of attributing m...
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08/19/2021
Mixture-Based Correction for Position and Trust Bias in Counterfactual Learning to Rank
In counterfactual learning to rank (CLTR) user interactions are used as ...
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06/30/2021
News Article Retrieval in Context for Event-centric Narrative Creation
Writers such as journalists often use automatic tools to find relevant c...
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06/29/2021