109 citations · 250 across the 18 of their papers we have counts for
20 papers
Self-supervised Meta-Prompt Learning with Meta-Gradient Regularization for Few-shot Generalization
Kaihang Pan, Juncheng Li, Hongye Song +3
Prompt tuning is a parameter-efficient method, which learns soft prompts and conditions frozen language models to perform specific downstream tasks. Though effective, prompt tuning…
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…
Dilated Context Integrated Network with Cross-Modal Consensus for Temporal Emotion Localization in Videos
Juncheng Li, Junlin Xie, Linchao Zhu +8
Understanding human emotions is a crucial ability for intelligent robots to provide better human-robot interactions. The existing works are limited to trimmed video-level emotion c…
Masked Autoencoders that Listen
Po-Yao Huang, Hu Xu, Juncheng Li +5
This paper studies a simple extension of image-based Masked Autoencoders (MAE) to self-supervised representation learning from audio spectrograms. Following the Transformer encoder…
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…