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03/27/2023
Revisiting Multimodal Representation in Contrastive Learning: From Patch and Token Embeddings to Finite Discrete Tokens
Contrastive learning-based vision-language pre-training approaches, such...
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09/30/2022
Intra-session Context-aware Feed Recommendation in Live Systems
Feed recommendation allows users to constantly browse items until feel u...
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09/12/2022
DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization
Device Model Generalization (DMG) is a practical yet under-investigated ...
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08/19/2022
Personalizing Intervened Network for Long-tailed Sequential User Behavior Modeling
In an era of information explosion, recommendation systems play an impor...
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08/04/2022
Prompt Tuning for Generative Multimodal Pretrained Models
Prompt tuning has become a new paradigm for model tuning and it has demo...
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07/19/2022
Single Stage Virtual Try-on via Deformable Attention Flows
Virtual try-on aims to generate a photo-realistic fitting result given a...
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07/07/2022
Device-Cloud Collaborative Recommendation via Meta Controller
On-device machine learning enables the lightweight deployment of recomme...
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06/29/2022
Knowledge Distillation of Transformer-based Language Models Revisited
In the past few years, transformer-based pre-trained language models hav...
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06/04/2022
Instance-wise Prompt Tuning for Pretrained Language Models
Prompt Learning has recently gained great popularity in bridging the gap...
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05/24/2022
M6-Fashion: High-Fidelity Multi-modal Image Generation and Editing
The fashion industry has diverse applications in multi-modal image gener...
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05/22/2022
GraphMAE: Self-Supervised Masked Graph Autoencoders
Self-supervised learning (SSL) has been extensively explored in recent y...
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05/17/2022
M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems
Industrial recommender systems have been growing increasingly complex, m...
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03/29/2022
In-N-Out Generative Learning for Dense Unsupervised Video Segmentation
In this paper, we focus on the unsupervised Video Object Segmentation (V...
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03/23/2022
Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably)
Despite the remarkable success of deep multi-modal learning in practice,...
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02/07/2022
Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
In this work, we pursue a unified paradigm for multimodal pretraining to...
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01/15/2022
Deep Unified Representation for Heterogeneous Recommendation
Recommendation system has been a widely studied task both in academia an...
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12/07/2021
Cross-domain User Preference Learning for Cold-start Recommendation
Cross-domain cold-start recommendation is an increasingly emerging issue...
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11/26/2021
KNAS: Green Neural Architecture Search
Many existing neural architecture search (NAS) solutions rely on downstr...
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11/11/2021
Edge-Cloud Polarization and Collaboration: A Comprehensive Survey
Influenced by the great success of deep learning via cloud computing and...
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10/08/2021
M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining
Recent expeditious developments in deep learning algorithms, distributed...
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10/08/2021
Stable Prediction on Graphs with Agnostic Distribution Shift
Graph is a flexible and effective tool to represent complex structures i...
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09/27/2021
Click-through Rate Prediction with Auto-Quantized Contrastive Learning
Click-through rate (CTR) prediction becomes indispensable in ubiquitous ...
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09/26/2021
Dynamic Sequential Graph Learning for Click-Through Rate Prediction
Click-through rate prediction plays an important role in the field of re...
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09/25/2021
MC^2-SF: Slow-Fast Learning for Mobile-Cloud Collaborative Recommendation
With the hardware development of mobile devices, it is possible to build...
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08/20/2021
Reinforcement Learning to Optimize Lifetime Value in Cold-Start Recommendation
Recommender system plays a crucial role in modern E-commerce platform. D...
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06/09/2021
Reliable Adversarial Distillation with Unreliable Teachers
In ordinary distillation, student networks are trained with soft labels ...
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06/02/2021
Learning to Rehearse in Long Sequence Memorization
Existing reasoning tasks often have an important assumption that the inp...
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05/31/2021
Controllable Gradient Item Retrieval
In this paper, we identify and study an important problem of gradient it...
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05/31/2021
Exploring Sparse Expert Models and Beyond
Mixture-of-Experts (MoE) models can achieve promising results with outra...
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05/31/2021
Connecting Language and Vision for Natural Language-Based Vehicle Retrieval
Vehicle search is one basic task for the efficient traffic management in...
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05/31/2021
Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation
Table-to-text generation refers to generating a descriptive text from a ...
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05/29/2021
UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis
Conditional image synthesis aims to create an image according to some mu...
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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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05/28/2021
Learning Relation Alignment for Calibrated Cross-modal Retrieval
Despite the achievements of large-scale multimodal pre-training approach...
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05/26/2021
CogView: Mastering Text-to-Image Generation via Transformers
Text-to-Image generation in the general domain has long been an open pro...
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05/24/2021
Federated Graph Learning – A Position Paper
Graph neural networks (GNN) have been successful in many fields, and der...
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05/17/2021
TCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning
Dynamic graph modeling has recently attracted much attention due to its ...
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04/14/2021
Device-Cloud Collaborative Learning for Recommendation
With the rapid development of storage and computing power on mobile devi...
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03/19/2021
Controllable Generation from Pre-trained Language Models via Inverse Prompting
Large-scale pre-trained language models have demonstrated strong capabil...
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03/17/2021
Learning with Group Noise
Machine learning in the context of noise is a challenging but practical ...
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03/03/2021
OAG-BERT: Pre-train Heterogeneous Entity-augmented Academic Language Model
To enrich language models with domain knowledge is crucial but difficult...
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03/01/2021
CogDL: An Extensive Toolkit for Deep Learning on Graphs
Graph representation learning aims to learn low-dimensional node embeddi...
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03/01/2021
M6: A Chinese Multimodal Pretrainer
In this work, we construct the largest dataset for multimodal pretrainin...
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02/18/2021
Dynamic Memory based Attention Network for Sequential Recommendation
Sequential recommendation has become increasingly essential in various o...
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02/18/2021
Sparse-Interest Network for Sequential Recommendation
Recent methods in sequential recommendation focus on learning an overall...
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02/10/2021
Inductive Granger Causal Modeling for Multivariate Time Series
Granger causal modeling is an emerging topic that can uncover Granger ca...
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02/06/2021
Understanding the Interaction of Adversarial Training with Noisy Labels
Noisy labels (NL) and adversarial examples both undermine trained models...
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09/28/2020
Graph-based Multi-hop Reasoning for Long Text Generation
Long text generation is an important but challenging task.The main probl...
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08/27/2020
