97 citations · 307 across the 22 of their papers we have counts for
6 papers · 1 filter
Audio-free Prompt Tuning for Language-Audio Models
Yiming Li, Xiangdong Wang, Hong Liu
Contrastive Language-Audio Pretraining (CLAP) is pre-trained to associate audio features with human language, making it a natural zero-shot classifier to recognize unseen sound cat…
Semi-supervised Sound Event Detection with Local and Global Consistency Regularization
Yiming Li, Xiangdong Wang, Hong Liu +3
Learning meaningful frame-wise features on a partially labeled dataset is crucial to semi-supervised sound event detection. Prior works either maintain consistency on frame-level p…
Towards Robust Model Watermark via Reducing Parametric Vulnerability
Guanhao Gan, Yiming Li, Dongxian Wu +1
Deep neural networks are valuable assets considering their commercial benefits and huge demands for costly annotation and computation resources. To protect the copyright of DNNs, b…
Towards Stealthy Backdoor Attacks against Speech Recognition via Elements of Sound
Hanbo Cai, Pengcheng Zhang, Hai Dong +3
Deep neural networks (DNNs) have been widely and successfully adopted and deployed in various applications of speech recognition. Recently, a few works revealed that these models a…
Backdoor Attack with Sparse and Invisible Trigger
Yinghua Gao, Yiming Li, Xueluan Gong +3
Deep neural networks (DNNs) are vulnerable to backdoor attacks, where the adversary manipulates a small portion of training data such that the victim model predicts normally on the…
SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency
Junfeng Guo, Yiming Li, Xun Chen +3
Deep neural networks (DNNs) are vulnerable to backdoor attacks, where adversaries embed a hidden backdoor trigger during the training process for malicious prediction manipulation.…