Maarten de Rijke

research

∙ 09/18/2023

Predictive Uncertainty-based Bias Mitigation in Ranking

Societal biases that are contained in retrieved documents have received ...

0 Maria Heuss, et al. ∙

research

∙ 08/29/2023

Continual Learning for Generative Retrieval over Dynamic Corpora

Generative retrieval (GR) directly predicts the identifiers of relevant ...

0 Jiangui Chen, et al. ∙

research

∙ 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 ...

0 Yu-An Liu, et al. ∙

research

∙ 08/05/2023

Group Membership Bias

When learning to rank from user interactions, search and recommendation ...

0 Ali Vardasbi, et al. ∙

research

∙ 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 ...

0 Ming Li, et al. ∙

research

∙ 07/08/2023

Answering Ambiguous Questions via Iterative Prompting

In open-domain question answering, due to the ambiguity of questions, mu...

0 Weiwei Sun, et al. ∙

research

∙ 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...

0 Gabriel Bénédict, et al. ∙

research

∙ 05/26/2023

Distributional Reinforcement Learning with Dual Expectile-Quantile Regression

Successful applications of distributional reinforcement learning with qu...

0 Sami Jullien, et al. ∙

research

∙ 05/22/2023

MultiTabQA: Generating Tabular Answers for Multi-Table Question Answering

Recent advances in tabular question answering (QA) with large language m...

0 Vaishali Pal, et al. ∙

research

∙ 05/18/2023

Query Performance Prediction: From Ad-hoc to Conversational Search

Query performance prediction (QPP) is a core task in information retriev...

0 Chuan Meng, et al. ∙

research

∙ 05/17/2023

Iteratively Learning Representations for Unseen Entities with Inter-Rule Correlations

Recent work on knowledge graph completion (KGC) focused on learning embe...

0 Zihan Wang, et al. ∙

research

∙ 05/09/2023

Improving Implicit Feedback-Based Recommendation through Multi-Behavior Alignment

Recommender systems that learn from implicit feedback often use large vo...

0 Xin Xin, et al. ∙

research

∙ 05/01/2023

On the Impact of Outlier Bias on User Clicks

User interaction data is an important source of supervision in counterfa...

0 Fatemeh Sarvi, et al. ∙

research

∙ 04/28/2023

Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models

Neural ranking models (NRMs) have attracted considerable attention in in...

0 Yu-An Liu, et al. ∙

research

∙ 04/28/2023

A Unified Generative Retriever for Knowledge-Intensive Language Tasks via Prompt Learning

Knowledge-intensive language tasks (KILTs) benefit from retrieving high-...

0 Jiangui Chen, et al. ∙

research

∙ 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 ...

0 Shashank Gupta, et al. ∙

research

∙ 04/19/2023

An Offline Metric for the Debiasedness of Click Models

A well-known problem when learning from user clicks are inherent biases ...

0 Romain Deffayet, et al. ∙

research

∙ 04/09/2023

Learning to Tokenize for Generative Retrieval

Conventional document retrieval techniques are mainly based on the index...

0 Weiwei Sun, et al. ∙

research

∙ 03/04/2023

A Self-Correcting Sequential Recommender

Sequential recommendations aim to capture users' preferences from their ...

0 Yujie Lin, et al. ∙

research

∙ 01/20/2023

Generative Slate Recommendation with Reinforcement Learning

Recent research has employed reinforcement learning (RL) algorithms to o...

0 Romain Deffayet, et al. ∙

research

∙ 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...

0 Mariya Hendriksen, et al. ∙

research

∙ 01/04/2023

Modeling Sequential Recommendation as Missing Information Imputation

Side information is being used extensively to improve the effectiveness ...

0 Yujie Lin, et al. ∙

research

∙ 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...

0 Romain Deffayet, et al. ∙

research

∙ 12/20/2022

Contrastive Learning Reduces Hallucination in Conversations

Pre-trained language models (LMs) store knowledge in their parameters an...

0 Weiwei Sun, et al. ∙

research

∙ 12/11/2022

Feature-Level Debiased Natural Language Understanding

Natural language understanding (NLU) models often rely on dataset biases...

16 Yougang Lyu, et al. ∙

research

∙ 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...

0 Sanne Vrijenhoek, et al. ∙

research

∙ 09/14/2022

Certified Robustness to Word Substitution Ranking Attack for Neural Ranking Models

Neural ranking models (NRMs) have achieved promising results in informat...

0 Chen Wu, et al. ∙

research

∙ 08/19/2022

Intersection of Parallels as an Early Stopping Criterion

A common way to avoid overfitting in supervised learning is early stoppi...

10 Ali Vardasbi, et al. ∙

research

∙ 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...

15 Ana Lucic, et al. ∙

research

∙ 06/24/2022

Debiasing Learning for Membership Inference Attacks Against Recommender Systems

Learned recommender systems may inadvertently leak information about the...

10 Zihan Wang, et al. ∙

research

∙ 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...

3 Sami Jullien, et al. ∙

research

∙ 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...

0 Maria Heuss, et al. ∙

research

∙ 05/10/2022

State Encoders in Reinforcement Learning for Recommendation: A Reproducibility Study

Methods for reinforcement learning for recommendation (RL4Rec) are incre...

0 Jin Huang, et al. ∙

research

∙ 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...

8 Shaojie Jiang, et al. ∙

research

∙ 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...

10 Ali Vardasbi, et al. ∙

research

∙ 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...

1 Maurits Bleeker, et al. ∙

research

∙ 04/26/2022

Understanding User Satisfaction with Task-oriented Dialogue Systems

Dialogue systems are evaluated depending on their type and purpose. Two ...

0 Clemencia Siro, et al. ∙

research

∙ 04/15/2022

Summarization with Graphical Elements

Automatic text summarization has experienced substantial progress in rec...

10 Maartje ter Hoeve, et al. ∙

research

∙ 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...

1 Vaishali Pal, et al. ∙

research

∙ 04/02/2022

Metaphorical User Simulators for Evaluating Task-oriented Dialogue Systems

Task-oriented dialogue systems (TDSs) are assessed mainly in an offline ...

1 Weiwei Sun, et al. ∙

research

∙ 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...

12 Maurits Bleeker, et al. ∙

research

∙ 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...

9 Mariya Hendriksen, et al. ∙

research

∙ 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...

0 Fatemeh Sarvi, et al. ∙

research

∙ 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...

0 Jin Huang, et al. ∙

research

∙ 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...

41 Ana Lucic, et al. ∙

research

∙ 09/29/2021

A Next Basket Recommendation Reality Check

The goal of a next basket recommendation (NBR) system is to recommend it...

11 Ming Li, et al. ∙

research

∙ 08/24/2021

sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel Classification

Multiclass multilabel classification refers to the task of attributing m...

29 Gabriel Bénédict, et al. ∙

research

∙ 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 ...

0 Ali Vardasbi, et al. ∙

research

∙ 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...

2 Nikos Voskarides, et al. ∙

research

∙ 06/29/2021

Few-Shot Electronic Health Record Coding through Graph Contrastive Learning

Electronic health record (EHR) coding is the task of assigning ICD codes...

24 Shanshan Wang, et al. ∙

Maarten de Rijke

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