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08/16/2023
Pro-Cap: Leveraging a Frozen Vision-Language Model for Hateful Meme Detection
Hateful meme detection is a challenging multimodal task that requires co...
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07/04/2023
Causal Reinforcement Learning: A Survey
Reinforcement learning is an essential paradigm for solving sequential d...
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05/29/2023
Continual Task Allocation in Meta-Policy Network via Sparse Prompting
How to train a generalizable meta-policy by continually learning a seque...
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05/27/2023
Modularized Zero-shot VQA with Pre-trained Models
Large-scale pre-trained models (PTMs) show great zero-shot capabilities....
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05/24/2023
Towards Cyber Security for Low-Carbon Transportation: Overview, Challenges and Future Directions
In recent years, low-carbon transportation has become an indispensable p...
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05/23/2023
Spatial-temporal Prompt Learning for Federated Weather Forecasting
Federated weather forecasting is a promising collaborative learning fram...
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04/09/2023
Does Continual Learning Equally Forget All Parameters?
Distribution shift (e.g., task or domain shift) in continual learning (C...
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03/14/2023
Adaptive Policy Learning for Offline-to-Online Reinforcement Learning
Conventional reinforcement learning (RL) needs an environment to collect...
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02/08/2023
Prompting for Multimodal Hateful Meme Classification
Hateful meme classification is a challenging multimodal task that requir...
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01/27/2023
Voting from Nearest Tasks: Meta-Vote Pruning of Pre-trained Models for Downstream Tasks
As a few large-scale pre-trained models become the major choices of vari...
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01/22/2023
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data
To tackle the global climate challenge, it urgently needs to develop a c...
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12/12/2022
P-Transformer: Towards Better Document-to-Document Neural Machine Translation
Directly training a document-to-document (Doc2Doc) neural machine transl...
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11/23/2022
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing
Graph neural networks (GNNs) have shown their superiority in modeling gr...
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10/08/2022
ngram-OAXE: Phrase-Based Order-Agnostic Cross Entropy for Non-Autoregressive Machine Translation
Recently, a new training oaxe loss has proven effective to ameliorate th...
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09/21/2022
Federated Learning from Pre-Trained Models: A Contrastive Learning Approach
Federated Learning (FL) is a machine learning paradigm that allows decen...
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08/17/2022
Disentangling Identity and Pose for Facial Expression Recognition
Facial expression recognition (FER) is a challenging problem because the...
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08/15/2022
Unsupervised Video Domain Adaptation: A Disentanglement Perspective
Unsupervised video domain adaptation is a practical yet challenging task...
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05/28/2022
Boosting Facial Expression Recognition by A Semi-Supervised Progressive Teacher
In this paper, we aim to improve the performance of in-the-wild Facial E...
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05/25/2022
On Secure NOMA-CDRT Systems with Physical Layer Network Coding
This paper proposes a new scheme to enhance the secrecy performance of a...
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05/20/2022
FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels
Federated learning (FL) aims at training a global model on the server si...
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04/21/2022
Joint Trajectory Design and User Scheduling of Aerial Cognitive Radio Networks
Unmanned aerial vehicles (UAVs) have been widely employed to enhance the...
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03/23/2022
An Empirical Study of Memorization in NLP
A recent study by Feldman (2020) proposed a long-tail theory to explain ...
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03/02/2022
Personalized Federated Learning With Structure
Knowledge sharing and model personalization are two key components to im...
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03/01/2022
Exploring and Adapting Chinese GPT to Pinyin Input Method
While GPT has become the de-facto method for text generation tasks, its ...
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02/21/2022
Applications of blockchain and artificial intelligence technologies for enabling prosumers in smart grids: A review
Governments' net zero emission target aims at increasing the share of re...
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02/13/2022
On the Convergence of Clustered Federated Learning
In a federated learning system, the clients, e.g. mobile devices and org...
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01/24/2022
Uplink Performance of High-Mobility Cell-Free Massive MIMO-OFDM Systems
High-speed train (HST) communications with orthogonal frequency division...
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10/24/2021
SCORE: Spurious COrrelation REduction for Offline Reinforcement Learning
Offline reinforcement learning (RL) aims to learn the optimal policy fro...
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09/29/2021
Digital Twins based Day-ahead Integrated Energy System Scheduling under Load and Renewable Energy Uncertainties
By constructing digital twins (DT) of an integrated energy system (IES),...
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09/07/2021
Sequential Diagnosis Prediction with Transformer and Ontological Representation
Sequential diagnosis prediction on the Electronic Health Record (EHR) ha...
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08/24/2021
Federated Learning for Privacy-Preserving Open Innovation Future on Digital Health
Privacy protection is an ethical issue with broad concern in Artificial ...
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08/24/2021
Federated Learning for Open Banking
Open banking enables individual customers to own their banking data, whi...
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08/15/2021
Complex Knowledge Base Question Answering: A Survey
Knowledge base question answering (KBQA) aims to answer a question over ...
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08/09/2021
Disentangling Hate in Online Memes
Hateful and offensive content detection has been extensively explored in...
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07/10/2021
Beyond Low-pass Filtering: Graph Convolutional Networks with Automatic Filtering
Graph convolutional networks are becoming indispensable for deep learnin...
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06/09/2021
Order-Agnostic Cross Entropy for Non-Autoregressive Machine Translation
We propose a new training objective named order-agnostic cross entropy (...
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05/25/2021
A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions
Knowledge base question answering (KBQA) aims to answer a question over ...
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05/01/2021
FedProto: Federated Prototype Learning over Heterogeneous Devices
The heterogeneity across devices usually hinders the optimization conver...
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02/03/2021
Isometric Propagation Network for Generalized Zero-shot Learning
Zero-shot learning (ZSL) aims to classify images of an unseen class only...
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01/19/2021
PICA: A Pixel Correlation-based Attentional Black-box Adversarial Attack
The studies on black-box adversarial attacks have become increasingly pr...
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01/19/2021
Attention-Guided Black-box Adversarial Attacks with Large-Scale Multiobjective Evolutionary Optimization
Fooling deep neural networks (DNNs) with the black-box optimization has ...
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01/11/2021
Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals
Multi-hop Knowledge Base Question Answering (KBQA) aims to find the answ...
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12/02/2020
SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning
Deep learning with noisy labels is a challenging task. Recent prominent ...
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11/06/2020
Confusable Learning for Large-class Few-Shot Classification
Few-shot image classification is challenging due to the lack of ample sa...
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11/04/2020
A BERT-based Dual Embedding Model for Chinese Idiom Prediction
Chinese idioms are special fixed phrases usually derived from ancient st...
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11/02/2020
Cooperative Heterogeneous Deep Reinforcement Learning
Numerous deep reinforcement learning agents have been proposed, and each...
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10/17/2020
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler
Imbalanced learning (IL), i.e., learning unbiased models from class-imba...
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10/12/2020
Counterfactual Variable Control for Robust and Interpretable Question Answering
Deep neural network based question answering (QA) models are neither rob...
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10/10/2020
RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion
Many graph embedding approaches have been proposed for knowledge graph c...
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10/07/2020
