collaborators

5 papers

cs.CV2026

CPR: Chained Perceptual Refinement for Coarse-to-Fine Medical Image Classification

Si-Yuan Lu, Hanruo Zhu, Ziquan Zhu +6

High resolution medical images contain fine grained, spatially sparse cues that are critical for diagnosis, yet preserving full resolution incurs substantial computational and memo…

cs.CE2026

Confusion-Aware Spectral Regularizer for Long-Tailed Recognition

Ziquan Zhu, Gaojie Jin, Hanruo Zhu +11

Long-tailed image classification remains a long-standing challenge, as real-world data typically follow highly imbalanced distributions where a few head classes dominate and many t…

cs.CE2026

Dual-Kernel Adapter: Expanding Spatial Horizons for Data-Constrained Medical Image Analysis

Ziquan Zhu, Hanruo Zhu, Siyuan Lu +8

Adapters have become a widely adopted strategy for efficient fine-tuning of large pretrained models, particularly in resource-constrained settings. However, their performance under…

cs.CE2025

LKA: Large Kernel Adapter for Enhanced Medical Image Classification

Ziquan Zhu, Si-Yuan Lu, Tianjin Huang +2

Despite the notable success of current Parameter-Efficient Fine-Tuning (PEFT) methods across various domains, their effectiveness on medical datasets falls short of expectations. T…

cs.LG2025

SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training

Tianjin Huang, Ziquan Zhu, Gaojie Jin +3

Large Language Models (LLMs) have demonstrated exceptional performance across diverse tasks, yet their training remains highly resource-intensive and susceptible to critical challe…