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09/16/2023
S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs
The traditional Dialogue State Tracking (DST) problem aims to track user...
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11/11/2022
Situating Recommender Systems in Practice: Towards Inductive Learning and Incremental Updates
With information systems becoming larger scale, recommendation systems a...
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07/07/2022
Learning Causal Effects on Hypergraphs
Hypergraphs provide an effective abstraction for modeling multi-way grou...
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01/10/2022
Learning Fair Node Representations with Graph Counterfactual Fairness
Fair machine learning aims to mitigate the biases of model predictions a...
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01/14/2020
BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network
Within-basket recommendation reduces the exploration time of users, wher...
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12/04/2019
Addressing Marketing Bias in Product Recommendations
Modern collaborative filtering algorithms seek to provide personalized p...
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08/27/2019
CosRec: 2D Convolutional Neural Networks for Sequential Recommendation
Sequential patterns play an important role in building modern recommende...
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05/31/2019
Fine-Grained Spoiler Detection from Large-Scale Review Corpora
This paper presents computational approaches for automatically detecting...
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11/26/2018
Beyond "How may I help you?": Assisting Customer Service Agents with Proactive Responses
We study the problem of providing recommended responses to customer serv...
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08/29/2018
Recommendation Through Mixtures of Heterogeneous Item Relationships
Recommender Systems have proliferated as general-purpose approaches to m...
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10/25/2016