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09/04/2023
Interactive Graph Convolutional Filtering
Interactive Recommender Systems (IRS) have been increasingly used in var...
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08/31/2023
Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations
Recommender models excel at providing domain-specific item recommendatio...
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08/15/2023
KMF: Knowledge-Aware Multi-Faceted Representation Learning for Zero-Shot Node Classification
Recently, Zero-Shot Node Classification (ZNC) has been an emerging and c...
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08/11/2023
Deep Task-specific Bottom Representation Network for Multi-Task Recommendation
Neural-based multi-task learning (MTL) has gained significant improvemen...
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07/31/2023
When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities
The advent of large language models marks a revolutionary breakthrough i...
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07/11/2023
A DeepLearning Framework for Dynamic Estimation of Origin-Destination Sequence
OD matrix estimation is a critical problem in the transportation domain....
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06/05/2023
Learning to Substitute Spans towards Improving Compositional Generalization
Despite the rising prevalence of neural sequence models, recent empirica...
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03/14/2023
Traffic4cast at NeurIPS 2022 – Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors
The global trends of urbanization and increased personal mobility force ...
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03/01/2023
GUESR: A Global Unsupervised Data-Enhancement with Bucket-Cluster Sampling for Sequential Recommendation
Sequential Recommendation is a widely studied paradigm for learning user...
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11/15/2022
Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation
Recent studies show that Graph Neural Networks(GNNs) are vulnerable and ...
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10/30/2022
Transposed Variational Auto-encoder with Intrinsic Feature Learning for Traffic Forecasting
In this technical report, we present our solutions to the Traffic4cast 2...
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10/25/2022
Towards Robust Recommender Systems via Triple Cooperative Defense
Recommender systems are often susceptible to well-crafted fake profiles,...
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06/28/2022
Cooperative Retriever and Ranker in Deep Recommenders
Deep recommender systems jointly leverage the retrieval and ranking oper...
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06/17/2022
Boosting Factorization Machines via Saliency-Guided Mixup
Factorization machines (FMs) are widely used in recommender systems due ...
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05/30/2022
Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever
Recommender retrievers aim to rapidly retrieve a fraction of items from ...
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04/27/2022
Self-Supervised Text Erasing with Controllable Image Synthesis
Recent efforts on scene text erasing have shown promising results. Howev...
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04/18/2022
HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization
In large-scale recommender systems, the user-item networks are generally...
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04/18/2022
BSAL: A Framework of Bi-component Structure and Attribute Learning for Link Prediction
Given the ubiquitous existence of graph-structured data, learning the re...
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04/01/2022
Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings
Vector quantization (VQ) based ANN indexes, such as Inverted File System...
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03/29/2022
Visualizing the Relationship Between Encoded Linguistic Information and Task Performance
Probing is popular to analyze whether linguistic information can be capt...
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03/29/2022
Investigating Data Variance in Evaluations of Automatic Machine Translation Metrics
Current practices in metric evaluation focus on one single dataset, e.g....
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02/28/2022
A Mutually Reinforced Framework for Pretrained Sentence Embeddings
The lack of labeled data is a major obstacle to learning high-quality se...
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01/23/2022
Reinforcement Routing on Proximity Graph for Efficient Recommendation
We focus on Maximum Inner Product Search (MIPS), which is an essential p...
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01/14/2022
Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval
Ad-hoc search calls for the selection of appropriate answers from a mass...
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10/26/2021
Meta-learning with an Adaptive Task Scheduler
To benefit the learning of a new task, meta-learning has been proposed t...
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09/13/2021
Fast Variational AutoEncoder with Inverted Multi-Index for Collaborative Filtering
Variational AutoEncoder (VAE) has been extended as a representative nonl...
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05/28/2021
Linear-Time Self Attention with Codeword Histogram for Efficient Recommendation
Self-attention has become increasingly popular in a variety of sequence ...
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05/28/2021
Rethinking Lifelong Sequential Recommendation with Incremental Multi-Interest Attention
Sequential recommendation plays an increasingly important role in many e...
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05/06/2021
Assessing Dialogue Systems with Distribution Distances
An important aspect of developing dialogue systems is how to evaluate an...
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04/22/2021
Hybrid Encoder: Towards Efficient and Precise Native AdsRecommendation via Hybrid Transformer Encoding Networks
Transformer encoding networks have been proved to be a powerful tool of ...
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04/16/2021
Search-oriented Differentiable Product Quantization
Product quantization (PQ) is a popular approach for maximum inner produc...
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03/02/2021
Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure
Ad creatives are one of the prominent mediums for online e-commerce adve...
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02/28/2021
Automated Creative Optimization for E-Commerce Advertising
Advertising creatives are ubiquitous in E-commerce advertisements and ae...
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02/08/2021
A Hybrid Bandit Model with Visual Priors for Creative Ranking in Display Advertising
Creative plays a great important role in e-commerce for exhibiting produ...
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11/02/2020
Sampling-Decomposable Generative Adversarial Recommender
Recommendation techniques are important approaches for alleviating infor...
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11/02/2020
Deep Pairwise Hashing for Cold-start Recommendation
Recommendation efficiency and data sparsity problems have been regarded ...
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05/24/2020
Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation
With the increasing availability of videos, how to edit them and present...
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05/12/2020
GoGNN: Graph of Graphs Neural Network for Predicting Structured Entity Interactions
Entity interaction prediction is essential in many important application...
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04/19/2020
Binarized Graph Neural Network
Recently, there have been some breakthroughs in graph analysis by applyi...
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07/15/2019
A Novel User Representation Paradigm for Making Personalized Candidate Retrieval
Candidate retrieval is a crucial part in recommendation system, where qu...
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06/05/2019
Binarized Collaborative Filtering with Distilling Graph Convolutional Networks
The efficiency of top-K item recommendation based on implicit feedback a...
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05/27/2019
MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network
Recently, the Network Representation Learning (NRL) techniques, which re...
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03/15/2019