research
∙
08/31/2023
Co-evolving Vector Quantization for ID-based Recommendation
Category information plays a crucial role in enhancing the quality and p...
share
research
∙
08/30/2023
DiffuVolume: Diffusion Model for Volume based Stereo Matching
Stereo matching is a significant part in many computer vision tasks and ...
research
∙
08/27/2023
Only Encode Once: Making Content-based News Recommender Greener
Large pretrained language models (PLM) have become de facto news encoder...
research
∙
08/20/2023
How Good Are Large Language Models at Out-of-Distribution Detection?
Out-of-distribution (OOD) detection plays a vital role in enhancing the ...
research
∙
08/13/2023
Estimator Meets Equilibrium Perspective: A Rectified Straight Through Estimator for Binary Neural Networks Training
Binarization of neural networks is a dominant paradigm in neural network...
research
∙
06/12/2023
Neighborhood-based Hard Negative Mining for Sequential Recommendation
Negative sampling plays a crucial role in training successful sequential...
research
∙
06/10/2023
Multi-modal Pre-training for Medical Vision-language Understanding and Generation: An Empirical Study with A New Benchmark
With the availability of large-scale, comprehensive, and general-purpose...
research
∙
06/08/2023
Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training
We consider the task of few-shot intent detection, which involves traini...
research
∙
04/09/2023
Continual Graph Convolutional Network for Text Classification
Graph convolutional network (GCN) has been successfully applied to captu...
research
∙
04/02/2023
FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation
User-curated item lists, such as video-based playlists on Youtube and bo...
research
∙
03/13/2023
SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency
This work presents an effective depth-consistency self-prompt Transforme...
research
∙
02/01/2023
Simple yet Effective Gradient-Free Graph Convolutional Networks
Linearized Graph Neural Networks (GNNs) have attracted great attention i...
research
∙
07/16/2022
Structural Prior Guided Generative Adversarial Transformers for Low-Light Image Enhancement
We propose an effective Structural Prior guided Generative Adversarial T...
research
∙
05/25/2022
New Intent Discovery with Pre-training and Contrastive Learning
New intent discovery aims to uncover novel intent categories from user u...
research
∙
05/15/2022
Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization
It is challenging to train a good intent classifier for a task-oriented ...
research
∙
02/14/2022
Online-updated High-order Collaborative Networks for Single Image Deraining
Single image deraining is an important and challenging task for some dow...
research
∙
02/12/2022
Modeling User Behavior with Graph Convolution for Personalized Product Search
User preference modeling is a vital yet challenging problem in personali...
research
∙
09/13/2021
Effectiveness of Pre-training for Few-shot Intent Classification
This paper investigates the effectiveness of pre-training for few-shot i...
research
∙
09/09/2021
Online Enhanced Semantic Hashing: Towards Effective and Efficient Retrieval for Streaming Multi-Modal Data
With the vigorous development of multimedia equipment and applications, ...
research
∙
08/24/2021
Adaptation-Agnostic Meta-Training
Many meta-learning algorithms can be formulated into an interleaved proc...
research
∙
06/17/2021
Embedding-based Product Retrieval in Taobao Search
Nowadays, the product search service of e-commerce platforms has become ...
research
∙
06/16/2021
Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training
Out-of-scope intent detection is of practical importance in task-oriente...
research
∙
02/18/2021
SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering
Medical visual question answering (Med-VQA) has tremendous potential in ...
research
∙
05/20/2020
M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems
Combining graph representation learning with multi-view data (side infor...
research
∙
03/03/2020
Self-Supervised Graph Representation Learning via Global Context Prediction
To take full advantage of fast-growing unlabeled networked data, this pa...
research
∙
12/26/2019
Variational Metric Scaling for Metric-Based Meta-Learning
Metric-based meta-learning has attracted a lot of attention due to its e...
research
∙
09/27/2019
Clustering Uncertain Data via Representative Possible Worlds with Consistency Learning
Clustering uncertain data is an essential task in data mining for the in...
research
∙
09/26/2019
Attributed Graph Learning with 2-D Graph Convolution
Graph convolutional neural networks have demonstrated promising performa...
research
∙
09/04/2019
Network Transfer Learning via Adversarial Domain Adaptation with Graph Convolution
This paper studies the problem of cross-network node classification to o...
research
∙
06/04/2019
Attributed Graph Clustering via Adaptive Graph Convolution
Attributed graph clustering is challenging as it requires joint modellin...
research
∙
01/28/2019
Generalized Label Propagation Methods for Semi-Supervised Learning
The key challenge in semi-supervised learning is how to effectively leve...
research
∙
07/08/2018
Large Margin Few-Shot Learning
The key issue of few-shot learning is learning to generalize. In this pa...
research
∙
01/22/2018