23 citations · 62 across the 10 of their papers we have counts for
5 papers · 1 filter
Error-aware Quantization through Noise Tempering
Zheng Wang, Juncheng B Li, Shuhui Qu +2
Quantization has become a predominant approach for model compression, enabling deployment of large models trained on GPUs onto smaller form-factor devices for inference. Quantizati…
SQuAT: Sharpness- and Quantization-Aware Training for BERT
Zheng Wang, Juncheng B Li, Shuhui Qu +2
Quantization is an effective technique to reduce memory footprint, inference latency, and power consumption of deep learning models. However, existing quantization methods suffer f…
Robustness of Neural Architectures for Audio Event Detection
Juncheng B Li, Zheng Wang, Shuhui Qu +1
Traditionally, in Audio Recognition pipeline, noise is suppressed by the "frontend", relying on preprocessing techniques such as speech enhancement. However, it is not guaranteed t…
On Adversarial Robustness of Large-scale Audio Visual Learning
Juncheng B Li, Shuhui Qu, Xinjian Li +2
As audio-visual systems are being deployed for safety-critical tasks such as surveillance and malicious content filtering, their robustness remains an under-studied area. Existing…
AudioTagging Done Right: 2nd comparison of deep learning methods for environmental sound classification
Juncheng B Li, Shuhui Qu, Po-Yao Huang +1
After its sweeping success in vision and language tasks, pure attention-based neural architectures (e.g. DeiT) are emerging to the top of audio tagging (AT) leaderboards, which see…