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09/06/2023
Zero-Resource Hallucination Prevention for Large Language Models
The prevalent use of large language models (LLMs) in various domains has...
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08/16/2023
Towards Personalized Federated Learning via Heterogeneous Model Reassembly
This paper focuses on addressing the practical yet challenging problem o...
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07/10/2023
Hate Speech Detection via Dual Contrastive Learning
The fast spread of hate speech on social media impacts the Internet envi...
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05/03/2023
On the Security Risks of Knowledge Graph Reasoning
Knowledge graph reasoning (KGR) – answering complex logical queries over...
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03/05/2023
Knowledge-Enhanced Semi-Supervised Federated Learning for Aggregating Heterogeneous Lightweight Clients in IoT
Federated learning (FL) enables multiple clients to train models collabo...
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02/21/2023
AutoML in The Wild: Obstacles, Workarounds, and Expectations
Automated machine learning (AutoML) is envisioned to make ML techniques ...
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11/05/2022
Forecasting User Interests Through Topic Tag Predictions in Online Health Communities
The increasing reliance on online communities for healthcare information...
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09/27/2022
Reasoning over Multi-view Knowledge Graphs
Recently, knowledge representation learning (KRL) is emerging as the sta...
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06/30/2022
Predicting Ulnar Collateral Ligament Injury in Rookie Major League Baseball Pitchers
In the growing world of machine learning and data analytics, scholars ar...
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05/09/2022
Price DOES Matter! Modeling Price and Interest Preferences in Session-based Recommendation
Session-based recommendation aims to predict items that an anonymous use...
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12/11/2021
MedAttacker: Exploring Black-Box Adversarial Attacks on Risk Prediction Models in Healthcare
Deep neural networks (DNNs) have been broadly adopted in health risk pre...
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09/12/2021
FedTriNet: A Pseudo Labeling Method with Three Players for Federated Semi-supervised Learning
Federated Learning has shown great potentials for the distributed data u...
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09/09/2021
FedCon: A Contrastive Framework for Federated Semi-Supervised Learning
Federated Semi-Supervised Learning (FedSSL) has gained rising attention ...
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06/22/2021
Multimodal Emergent Fake News Detection via Meta Neural Process Networks
Fake news travels at unprecedented speeds, reaches global audiences and ...
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05/25/2021
Writing by Memorizing: Hierarchical Retrieval-based Medical Report Generation
Medical report generation is one of the most challenging tasks in medica...
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05/07/2021
ConCAD: Contrastive Learning-based Cross Attention for Sleep Apnea Detection
With recent advancements in deep learning methods, automatically learnin...
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05/05/2021
SafeDrug: Dual Molecular Graph Encoders for Safe Drug Recommendations
Medication recommendation is an essential task of AI for healthcare. Exi...
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03/17/2021
Fairness-aware Outlier Ensemble
Outlier ensemble methods have shown outstanding performance on the disco...
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01/22/2021
i-Algebra: Towards Interactive Interpretability of Deep Neural Networks
Providing explanations for deep neural networks (DNNs) is essential for ...
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12/06/2020
FedSemi: An Adaptive Federated Semi-Supervised Learning Framework
Federated learning (FL) has emerged as an effective technique to co-trai...
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12/04/2020
A Benchmark Dataset for Understandable Medical Language Translation
In this paper, we introduce MedLane – a new human-annotated Medical Lang...
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10/22/2020
UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data
Successful health risk prediction demands accuracy and reliability of th...
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08/16/2020
Efficient Knowledge Graph Validation via Cross-Graph Representation Learning
Recent advances in information extraction have motivated the automatic c...
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12/28/2019
Weak Supervision for Fake News Detection via Reinforcement Learning
Today social media has become the primary source for news. Via social me...
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06/20/2019
Multi-Grained Named Entity Recognition
This paper presents a novel framework, MGNER, for Multi-Grained Named En...
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07/06/2017
