Search Results for author: Xiaobing Feng

Found 10 papers, 1 papers with code

Output Constraints as Attack Surface: Exploiting Structured Generation to Bypass LLM Safety Mechanisms

no code implementations31 Mar 2025 Shuoming Zhang, Jiacheng Zhao, Ruiyuan Xu, Xiaobing Feng, Huimin Cui

In this work, we reveal a critical control-plane attack surface orthogonal to traditional data-plane vulnerabilities.

M4: Multi-Proxy Multi-Gate Mixture of Experts Network for Multiple Instance Learning in Histopathology Image Analysis

1 code implementation24 Jul 2024 Junyu Li, Ye Zhang, Wen Shu, Xiaobing Feng, Yingchun Wang, Pengju Yan, Xiaolin Li, Chulin Sha, Min He

Multiple instance learning (MIL) has been successfully applied for whole slide images (WSIs) analysis in computational pathology, enabling a wide range of prediction tasks from tumor subtyping to inferring genetic mutations and multi-omics biomarkers.

Mixture-of-Experts Multiple Instance Learning +2

Improving Speech Recognition Accuracy of Local POI Using Geographical Models

no code implementations7 Jul 2021 Songjun Cao, Yike Zhang, Xiaobing Feng, Long Ma

Secondly, a group of geo-specific language models (Geo-LMs) are integrated into our speech recognition system to improve recognition accuracy of long tail and homophone POI.

speech-recognition Speech Recognition

Pinpointing the Memory Behaviors of DNN Training

no code implementations1 Apr 2021 Jiansong Li, Xiao Dong, Guangli Li, Peng Zhao, Xueying Wang, Xiaobing Chen, Xianzhi Yu, Yongxin Yang, Zihan Jiang, Wei Cao, Lei Liu, Xiaobing Feng

The training of deep neural networks (DNNs) is usually memory-hungry due to the limited device memory capacity of DNN accelerators.

Fusion-Catalyzed Pruning for Optimizing Deep Learning on Intelligent Edge Devices

no code implementations30 Oct 2020 Guangli Li, Xiu Ma, Xueying Wang, Lei Liu, Jingling Xue, Xiaobing Feng

The increasing computational cost of deep neural network models limits the applicability of intelligent applications on resource-constrained edge devices.

Network Pruning

Auto-tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge

no code implementations16 Dec 2018 Guangli Li, Lei Liu, Xueying Wang, Xiao Dong, Peng Zhao, Xiaobing Feng

By analyzing the characteristics of layers in DNNs, an auto-tuning neural network quantization framework for collaborative inference is proposed.

Collaborative Inference Quantization

Group Orbit Optimization: A Unified Approach to Data Normalization

no code implementations3 Oct 2014 Shuchang Zhou, Zhihua Zhang, Xiaobing Feng

In this paper we propose and study an optimization problem over a matrix group orbit that we call \emph{Group Orbit Optimization} (GOO).

Tensor Decomposition

Cannot find the paper you are looking for? You can Submit a new open access paper.