activity
20182025
most citedCorrelation Congruence for Knowledge Distillation

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

collaborators

7 papers

cs.CL2025

Rhea: Role-aware Heuristic Episodic Attention for Conversational LLMs

Wanyang Hong, Zhaoning Zhang, Yi Chen +5

Large Language Models (LLMs) have achieved remarkable performance on single-turn tasks, yet their effectiveness deteriorates in multi-turn conversations. We define this phenomenon…

cs.CL2024

Dovetail: A CPU/GPU Heterogeneous Speculative Decoding for LLM inference

Libo Zhang, Zhaoning Zhang, Baizhou Xu +4

With the continuous advancement in the performance of large language models (LLMs), their demand for computational resources and memory has significantly increased, which poses maj…

cs.CV20193 cited

Correlation Congruence for Knowledge Distillation

Baoyun Peng, Xiao Jin, Jiaheng Liu +5

Most teacher-student frameworks based on knowledge distillation (KD) depend on a strong congruent constraint on instance level. However, they usually ignore the correlation between…

cs.CV2018

Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors

Hao Yu, Zhaoning Zhang, Zheng Qin +4

Modern object detectors usually suffer from low accuracy issues, as foregrounds always drown in tons of backgrounds and become hard examples during training. Compared with those pr…

cs.CV2018

Diagonalwise Refactorization: An Efficient Training Method for Depthwise Convolutions

Zheng Qin, Zhaoning Zhang, Dongsheng Li +2

Depthwise convolutions provide significant performance benefits owing to the reduction in both parameters and mult-adds. However, training depthwise convolution layers with GPUs is…

cs.CV2018

Merging and Evolution: Improving Convolutional Neural Networks for Mobile Applications

Zheng Qin, Zhaoning Zhang, Shiqing Zhang +2

Compact neural networks are inclined to exploit "sparsely-connected" convolutions such as depthwise convolution and group convolution for employment in mobile applications. Compare…