Yao Lu

According to our database, Yao Lu authored at least 28 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

LoRALib: A Standardized Benchmark for Evaluating LoRA-MoE Methods.

Shaoheng Wang, Yao Lu, Yuqi Li, Yaxin Gao, Jiaqi Nie, Shanqing Yu, Yingli Tian, Qi Xuan

CoRR, September, 2025

DSPC: Dual-Stage Progressive Compression Framework for Efficient Long-Context Reasoning.

Yaxin Gao, Yao Lu, Zongfei Zhang, Jiaqi Nie, Shanqing Yu, Qi Xuan

CoRR, September, 2025

SelectMix: Enhancing Label Noise Robustness through Targeted Sample Mixing.

Qiuhao Liu, Ling Li, Yao Lu, Qi Xuan, Zhaowei Zhu, Jiaheng Wei

CoRR, September, 2025

<i>FoQuS</i>: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition.

Yao Lu, Chunfeng Sun, Dongwei Xu, Yun Lin, Qi Xuan, Guan Gui

CoRR, September, 2025

A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models.

Yao Lu, Yutao Zhu, Yuqi Li, Dongwei Xu, Yun Lin, Qi Xuan, Xiaoniu Yang

IEEE Trans. Cogn. Commun. Netw., August, 2025

DUSE: A Data Expansion Framework for Low-resource Automatic Modulation Recognition based on Active Learning.

Yao Lu, Hongyu Gao, Zhuangzhi Chen, Dongwei Xu, Yun Lin, Qi Xuan, Guan Gui

CoRR, July, 2025

From LLM-anation to LLM-orchestrator: Coordinating Small Models for Data Labeling.

Yao Lu, Zhaiyuan Ji, Jiawei Du, Shanqing Yu, Qi Xuan, Tianyi Zhou

CoRR, June, 2025

ReStNet: A Reusable & Stitchable Network for Dynamic Adaptation on IoT Devices.

Maoyu Wang, Yao Lu, Jiaqi Nie, Zeyu Wang, Yun Lin, Qi Xuan, Guan Gui

CoRR, June, 2025

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition.

Yao Lu, Tengfei Ma, Zeyu Wang, Zhuangzhi Chen, Dongwei Xu, Yun Lin, Qi Xuan, Guan Gui

CoRR, May, 2025

SepPrune: Structured Pruning for Efficient Deep Speech Separation.

Yuqi Li, Kai Li, Xin Yin, Zhifei Yang, Junhao Dong, Zeyu Dong, Chuanguang Yang, Yingli Tian, Yao Lu

CoRR, May, 2025

MCLRL: A Multi-Domain Contrastive Learning with Reinforcement Learning Framework for Few-Shot Modulation Recognition.

Dongwei Xu, Yutao Zhu, Yao Lu, Youpeng Feng, Yun Lin, Qi Xuan

CoRR, February, 2025

Knowledge-enhanced Relation Graph and Task Sampling for few-shot molecular property prediction.

Zeyu Wang, Tianyi Jiang, Yao Lu, Xiaoze Bao, Shanqing Yu, Bin Wei, Qi Xuan, Hong Wang

Inf. Sci., 2025

Graph-Based Similarity of Deep Neural Networks.

Zuohui Chen, Yao Lu, Jinxuan Hu, Qi Xuan, Zhen Wang, Xiaoniu Yang

Neurocomputing, 2025

2024

RGP: Neural Network Pruning Through Regular Graph With Edges Swapping.

Zhuangzhi Chen, Jingyang Xiang, Yao Lu, Qi Xuan, Zhen Wang, Guanrong Chen, Xiaoniu Yang

IEEE Trans. Neural Networks Learn. Syst., October, 2024

Efficient Parallel Genetic Algorithm for Perturbed Substructure Optimization in Complex Network.

Shanqing Yu, Meng Zhou, Jintao Zhou, Minghao Zhao, Yidan Song, Yao Lu, Zeyu Wang, Qi Xuan

CoRR, 2024

Reassessing Layer Pruning in LLMs: New Insights and Methods.

Yao Lu, Hao Cheng, Yujie Fang, Zeyu Wang, Jiaheng Wei, Dongwei Xu, Qi Xuan, Xiaoniu Yang, Zhaowei Zhu

CoRR, 2024

RedTest: Towards Measuring Redundancy in Deep Neural Networks Effectively.

Yao Lu, Peixin Zhang, Jingyi Wang, Lei Ma, Xiaoniu Yang, Qi Xuan

CoRR, 2024

MDM: Advancing Multi-Domain Distribution Matching for Automatic Modulation Recognition Dataset Synthesis.

Dongwei Xu, Jiajun Chen, Yao Lu, Tianhao Xia, Qi Xuan, Wei Wang, Yun Lin, Xiaoniu Yang

CoRR, 2024

Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property Prediction.

Zeyu Wang, Tianyi Jiang, Yao Lu, Xiaoze Bao, Shanqing Yu, Bin Wei, Qi Xuan

CoRR, 2024

How Does Contrastive Learning Organize Images?

Yunzhe Zhang, Yao Lu, Qi Xuan

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2024

RK-CORE: An Established Methodology for Exploring the Hierarchical Structure within Datasets.

Yao Lu, Yutian Huang, Jiaqi Nie, Zuohui Chen, Qi Xuan

Proceedings of the IEEE International Conference on Acoustics, 2024

Exploring the Impact of Dataset Bias on Dataset Distillation.

Yao Lu, Jianyang Gu, Xuguang Chen, Saeed Vahidian, Qi Xuan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Can pre-trained models assist in dataset distillation?

Yao Lu, Xuguang Chen, Yuchen Zhang, Jianyang Gu, Tianle Zhang, Yifan Zhang, Xiaoniu Yang, Qi Xuan, Kai Wang, Yang You

CoRR, 2023

Exploring Inductive Biases in Contrastive Learning: A Clustering Perspective.

Yunzhe Zhang, Yao Lu, Lei Xu, Kunlin Yang, Hui Tang, Shuyuan Ye, Qi Xuan

CoRR, 2023

SR-init: An Interpretable Layer Pruning Method.

Hui Tang, Yao Lu, Qi Xuan

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Understanding the Dynamics of DNNs Using Graph Modularity.

Yao Lu, Wen Yang, Yunzhe Zhang, Zuohui Chen, Jinyin Chen, Qi Xuan, Zhen Wang, Xiaoniu Yang

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Graph-Based Similarity of Neural Network Representations.

Zuohui Chen, Yao Lu, Wen Yang, Qi Xuan, Xiaoniu Yang

CoRR, 2021

RGP: Neural Network Pruning through Its Regular Graph Structure.

Zhuangzhi Chen, Jingyang Xiang, Yao Lu, Qi Xuan

CoRR, 2021