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08/29/2023
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks
As powerful tools for representation learning on graphs, graph neural ne...
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06/07/2023
PromptAttack: Probing Dialogue State Trackers with Adversarial Prompts
A key component of modern conversational systems is the Dialogue State T...
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05/11/2023
Automated Data Denoising for Recommendation
In real-world scenarios, most platforms collect both large-scale, natura...
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02/13/2023
Enhancing User Personalization in Conversational Recommenders
Conversational recommenders are emerging as a powerful tool to personali...
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01/26/2023
Evolution of Filter Bubbles and Polarization in News Recommendation
Recent work in news recommendation has demonstrated that recommenders ca...
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10/13/2022
Closed-book Question Generation via Contrastive Learning
Question Generation (QG) is a fundamental NLP task for many downstream a...
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08/08/2022
Towards Fair Conversational Recommender Systems
Conversational recommender systems have demonstrated great success. They...
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08/05/2022
Quantifying and Mitigating Popularity Bias in Conversational Recommender Systems
Conversational recommender systems (CRS) have shown great success in acc...
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07/07/2022
Evolution of Popularity Bias: Empirical Study and Debiasing
Popularity bias is a long-standing challenge in recommender systems. Suc...
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03/14/2022
MetaBalance: Improving Multi-Task Recommendations via Adapting Gradient Magnitudes of Auxiliary Tasks
In many personalized recommendation scenarios, the generalization abilit...
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12/28/2021
Session-based Recommendation with Hypergraph Attention Networks
Session-based recommender systems aim to improve recommendations in shor...
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07/13/2021
Sequential Recommendation for Cold-start Users with Meta Transitional Learning
A fundamental challenge for sequential recommenders is to capture the se...
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07/07/2021
Identifying Hijacked Reviews
Fake reviews and review manipulation are growing problems on online mark...
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04/08/2021
Predicting the Reproducibility of Social and Behavioral Science Papers Using Supervised Learning Models
In recent years, significant effort has been invested verifying the repr...
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03/14/2021
Fairness-aware Personalized Ranking Recommendation via Adversarial Learning
Recommendation algorithms typically build models based on historical use...
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10/08/2020
Infusing Disease Knowledge into BERT for Health Question Answering, Medical Inference and Disease Name Recognition
Knowledge of a disease includes information of various aspects of the di...
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10/08/2020
PARADE: A New Dataset for Paraphrase Identification Requiring Computer Science Domain Knowledge
We present a new benchmark dataset called PARADE for paraphrase identifi...
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02/06/2020
Understanding Car-Speak: Replacing Humans in Dealerships
A large portion of the car-buying experience in the United States involv...
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12/30/2019
Consistency-Aware Recommendation for User-Generated ItemList Continuation
User-generated item lists are popular on many platforms. Examples includ...
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12/30/2019
A Hierarchical Self-Attentive Model for Recommending User-Generated Item Lists
User-generated item lists are a popular feature of many different platfo...
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01/03/2019
Pseudo-Implicit Feedback for Alleviating Data Sparsity in Top-K Recommendation
We propose PsiRec, a novel user preference propagation recommender that ...
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09/09/2018
Fairness-Aware Recommendation of Information Curators
This paper highlights our ongoing efforts to create effective informatio...
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11/28/2017
Tensor Completion Algorithms in Big Data Analytics
Tensor completion is a problem of filling the missing or unobserved entr...
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07/28/2017