most citedSurvey on Knowledge Distillation for Large Language Models: Methods, Evaluation, and Application

2 citations · 3 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV20241 cited

An Efficient Framework for Enhancing Discriminative Models via Diffusion Techniques

Chunxiao Li, Xiaoxiao Wang, Boming Miao +3

Image classification serves as the cornerstone of computer vision, traditionally achieved through discriminative models based on deep neural networks. Recent advancements have intr…

cs.CL20242 cited

Survey on Knowledge Distillation for Large Language Models: Methods, Evaluation, and Application

Chuanpeng Yang, Wang Lu, Yao Zhu +5

Large Language Models (LLMs) have showcased exceptional capabilities in various domains, attracting significant interest from both academia and industry. Despite their impressive p…

cs.CV2023

COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts

Xiaofeng Mao, Yuefeng Chen, Yao Zhu +4

Practical object detection application can lose its effectiveness on image inputs with natural distribution shifts. This problem leads the research community to pay more attention…

eess.IV20231 cited

Green Steganalyzer: A Green Learning Approach to Image Steganalysis

Yao Zhu, Xinyu Wang, Hong-Shuo Chen +2

A novel learning solution to image steganalysis based on the green learning paradigm, called Green Steganalyzer (GS), is proposed in this work. GS consists of three modules: 1) pix…

cs.CV2023

ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing

Xiaodan Li, Yuefeng Chen, Yao Zhu +3

Recent studies have shown that higher accuracy on ImageNet usually leads to better robustness against different corruptions. Therefore, in this paper, instead of following the trad…

cs.SD2023

TransAudio: Towards the Transferable Adversarial Audio Attack via Learning Contextualized Perturbations

Qi Gege, Yuefeng Chen, Xiaofeng Mao +5

In a transfer-based attack against Automatic Speech Recognition (ASR) systems, attacks are unable to access the architecture and parameters of the target model. Existing attack met…