most citedDescribe Anything in Medical Images

2 citations · 2 across the 7 of their papers we have counts for

collaborators

17 papers

cs.CV2025

Self-Supervised Visual Prompting for Cross-Domain Road Damage Detection

Xi Xiao, Zhuxuanzi Wang, Mingqiao Mo +6

The deployment of automated pavement defect detection is often hindered by poor cross-domain generalization. Supervised detectors achieve strong in-domain accuracy but require cost…

cs.LG2025

Learning Straight Flows: Variational Flow Matching for Efficient Generation

Chenrui Ma, Xi Xiao, Tianyang Wang +2

Flow Matching has limited ability in achieving one-step generation due to its reliance on learned curved trajectories. Previous studies have attempted to address this limitation by…

cs.LG2025

CTR-LoRA: Curvature-Aware and Trust-Region Guided Low-Rank Adaptation for Large Language Models

Zhuxuanzi Wang, Mingqiao Mo, Xi Xiao +6

Parameter-efficient fine-tuning (PEFT) has become the standard approach for adapting large language models under limited compute and memory budgets. Although previous methods impro…

cs.CV2025

Towards Foundation Models for Cryo-ET Subtomogram Analysis

Runmin Jiang, Wanyue Feng, Yuntian Yang +11

Cryo-electron tomography (cryo-ET) enables in situ visualization of macromolecular structures, where subtomogram analysis tasks such as classification, alignment, and averaging are…

cs.LG2025

HyperAdaLoRA: Accelerating LoRA Rank Allocation During Training via Hypernetworks without Sacrificing Performance

Hao Zhang, Zhenjia Li, Runfeng Bao +8

Parameter-Efficient Fine-Tuning (PEFT), especially Low-Rank Adaptation (LoRA), has emerged as a promising approach to fine-tuning large language models(LLMs) while reducing computa…

cs.CV2025

Stochastic Interpolants via Conditional Dependent Coupling

Chenrui Ma, Xi Xiao, Tianyang Wang +2

Existing image generation models face critical challenges regarding the trade-off between computation and fidelity. Specifically, models relying on a pretrained Variational Autoenc…