6 papers · 1 filter
Adapting Vision Foundation Models with Cascaded Semantics
Xi Xiao, Xingjian Li, Cheng Han +8
Prompt tuning, a leading parameter-efficient adaptation paradigm in NLP, has recently been extended to computer vision. Visual prompt tuning (VPT) adapts pre-trained vision transfo…
Layer-Specific Prompt Fusion Discovery via Differentiable Search in Vision Foundation Models
Xi Xiao, Xingjian Li, Yunbei Zhang +7
Visual prompt tuning has emerged as a parameter-efficient fine-tuning approach for adapting large-scale Vision Transformers (ViTs) to downstream tasks. As its learnable prompts are…
Mind the Rarities: Can Rare Skin Diseases Be Reliably Diagnosed via Diagnostic Reasoning?
Yang Liu, Jiyao Yang, Hongjin Zhao +10
Large vision-language models (LVLMs) demonstrate strong performance in dermatology; however, evaluating diagnostic reasoning for rare conditions remains largely unexplored. Existin…
SG-OIF: A Stability-Guided Online Influence Framework for Reliable Vision Data
Penghao Rao, Runmin Jiang, Min Xu
Approximating training-point influence on test predictions is critical for deploying deep-learning vision models, essential for locating noisy data. Though the influence function w…
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…
CryoCCD: Conditional Cycle-consistent Diffusion with Biophysical Modeling for Cryo-EM Synthesis
Runmin Jiang, Genpei Zhang, Yuntian Yang +10
Single-particle cryo-electron microscopy (cryo-EM) has become a cornerstone of structural biology, enabling near-atomic resolution analysis of macromolecules through advanced compu…