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08/07/2023
Learning Concise and Descriptive Attributes for Visual Recognition
Recent advances in foundation models present new opportunities for inter...
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05/24/2023
Debiasing Made State-of-the-art: Revisiting the Simple Seed-based Weak Supervision for Text Classification
Recent advances in weakly supervised text classification mostly focus on...
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05/24/2023
SELFOOD: Self-Supervised Out-Of-Distribution Detection via Learning to Rank
Deep neural classifiers trained with cross-entropy loss (CE loss) often ...
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04/17/2023
Bridging Discrete and Backpropagation: Straight-Through and Beyond
Backpropagation, the cornerstone of deep learning, is limited to computi...
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02/02/2023
Generalized Uncertainty of Deep Neural Networks: Taxonomy and Applications
Deep neural networks have seen enormous success in various real-world ap...
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06/14/2022
SoTeacher: A Student-oriented Teacher Network Training Framework for Knowledge Distillation
How to train an ideal teacher for knowledge distillation is still an ope...
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05/25/2022
LOPS: Learning Order Inspired Pseudo-Label Selection for Weakly Supervised Text Classification
Weakly supervised text classification methods typically train a deep neu...
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12/16/2021
A Heterogeneous Graph Learning Model for Cyber-Attack Detection
A cyber-attack is a malicious attempt by experienced hackers to breach t...
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10/07/2021
Double Descent in Adversarial Training: An Implicit Label Noise Perspective
Here, we show that the robust overfitting shall be viewed as the early p...
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09/22/2021
BFClass: A Backdoor-free Text Classification Framework
Backdoor attack introduces artificial vulnerabilities into the model by ...
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04/18/2021
"Average" Approximates "First Principal Component"? An Empirical Analysis on Representations from Neural Language Models
Contextualized representations based on neural language models have furt...
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02/15/2021
Data Profiling for Adversarial Training: On the Ruin of Problematic Data
Multiple intriguing problems hover in adversarial training, including ro...
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10/15/2020