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07/29/2023
Towards Codable Text Watermarking for Large Language Models
As large language models (LLMs) generate texts with increasing fluency a...
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05/21/2023
Communication Efficient Federated Learning for Multilingual Neural Machine Translation with Adapter
Federated Multilingual Neural Machine Translation (Fed-MNMT) has emerged...
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01/30/2023
Fine-Tuning Deteriorates General Textual Out-of-Distribution Detection by Distorting Task-Agnostic Features
Detecting out-of-distribution (OOD) inputs is crucial for the safe deplo...
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01/25/2023
When to Trust Aggregated Gradients: Addressing Negative Client Sampling in Federated Learning
Federated Learning has become a widely-used framework which allows learn...
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01/25/2023
Integrating Local Real Data with Global Gradient Prototypes for Classifier Re-Balancing in Federated Long-Tailed Learning
Federated Learning (FL) has become a popular distributed learning paradi...
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10/14/2022
Expose Backdoors on the Way: A Feature-Based Efficient Defense against Textual Backdoor Attacks
Natural language processing (NLP) models are known to be vulnerable to b...
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10/15/2021
RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Models
Backdoor attacks, which maliciously control a well-trained model's outpu...
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10/13/2021
Well-classified Examples are Underestimated in Classification with Deep Neural Networks
The conventional wisdom behind learning deep classification models is to...
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03/29/2021