19 citations · 92 across the 16 of their papers we have counts for
16 papers
Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models
Huachuan Qiu, Shuai Zhang, Anqi Li +2
Considerable research efforts have been devoted to ensuring that large language models (LLMs) align with human values and generate safe text. However, an excessive focus on sensiti…
A Benchmark for Understanding Dialogue Safety in Mental Health Support
Huachuan Qiu, Tong Zhao, Anqi Li +3
Dialogue safety remains a pervasive challenge in open-domain human-machine interaction. Existing approaches propose distinctive dialogue safety taxonomies and datasets for detectin…
Understanding Client Reactions in Online Mental Health Counseling
Anqi Li, Lizhi Ma, Yaling Mei +4
Communication success relies heavily on reading participants' reactions. Such feedback is especially important for mental health counselors, who must carefully consider the client'…
Clustering COVID-19 Lung Scans
Jacob Householder, Andrew Householder, John Paul Gomez-Reed +2
With the ongoing COVID-19 pandemic, understanding the characteristics of the virus has become an important and challenging task in the scientific community. While tests do exist fo…
Automated Radiological Report Generation For Chest X-Rays With Weakly-Supervised End-to-End Deep Learning
Shuai Zhang, Xiaoyan Xin, Yang Wang +7
The chest X-Ray (CXR) is the one of the most common clinical exam used to diagnose thoracic diseases and abnormalities. The volume of CXR scans generated daily in hospitals is huge…
Weakly-Supervised Degree of Eye-Closeness Estimation
Eyasu Mequanint, Shuai Zhang, Bijan Forutanpour +2
Following recent technological advances there is a growing interest in building non-intrusive methods that help us communicate with computing devices. In this regard, accurate info…
Trained Rank Pruning for Efficient Deep Neural Networks
Yuhui Xu, Yuxi Li, Shuai Zhang +7
To accelerate DNNs inference, low-rank approximation has been widely adopted because of its solid theoretical rationale and efficient implementations. Several previous works attemp…
AutoShuffleNet: Learning Permutation Matrices via an Exact Lipschitz Continuous Penalty in Deep Convolutional Neural Networks
Jiancheng Lyu, Shuai Zhang, Yingyong Qi +1
ShuffleNet is a state-of-the-art light weight convolutional neural network architecture. Its basic operations include group, channel-wise convolution and channel shuffling. However…
DAC: Data-free Automatic Acceleration of Convolutional Networks
Xin Li, Shuai Zhang, Bolan Jiang +3
Deploying a deep learning model on mobile/IoT devices is a challenging task. The difficulty lies in the trade-off between computation speed and accuracy. A complex deep learning mo…
DNQ: Dynamic Network Quantization
Yuhui Xu, Shuai Zhang, Yingyong Qi +3
Network quantization is an effective method for the deployment of neural networks on memory and energy constrained mobile devices. In this paper, we propose a Dynamic Network Quant…
Trained Rank Pruning for Efficient Deep Neural Networks
Yuhui Xu, Yuxi Li, Shuai Zhang +6
The performance of Deep Neural Networks (DNNs) keeps elevating in recent years with increasing network depth and width. To enable DNNs on edge devices like mobile phones, researche…
Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks
Penghang Yin, Shuai Zhang, Jiancheng Lyu +3
Quantized deep neural networks (QDNNs) are attractive due to their much lower memory storage and faster inference speed than their regular full precision counterparts. To maintain…
Quantization and Training of Low Bit-Width Convolutional Neural Networks for Object Detection
Penghang Yin, Shuai Zhang, Yingyong Qi +1
We present LBW-Net, an efficient optimization based method for quantization and training of the low bit-width convolutional neural networks (CNNs). Specifically, we quantize the we…
Transformed Schatten-1 Iterative Thresholding Algorithms for Low Rank Matrix Completion
Shuai Zhang, Penghang Yin, Jack Xin
We study a non-convex low-rank promoting penalty function, the transformed Schatten-1 (TS1), and its applications in matrix completion. The TS1 penalty, as a matrix quasi-norm defi…
Minimization of Transformed Penalty: Closed Form Representation and Iterative Thresholding Algorithms
Shuai Zhang, Jack Xin
The transformed penalty (TL1) functions are a one parameter family of bilinear transformations composed with the absolute value function. When acting on vectors, the TL1 pena…
Minimization of Transformed Penalty: Theory, Difference of Convex Function Algorithm, and Robust Application in Compressed Sensing
Shuai Zhang, Jack Xin
We study the minimization problem of a non-convex sparsity promoting penalty function, the transformed (TL1), and its application in compressed sensing (CS). The TL1 penalty…