3 papers
cs.CV2026
Geometric Decoupling: Diagnosing the Structural Instability of Latent
Yuanbang Liang, Zhengwen Chen, Yu-Kun Lai
Latent Diffusion Models (LDMs) achieve high-fidelity synthesis but suffer from latent space brittleness, causing discontinuous semantic jumps during editing. We introduce a Riemann…
cs.CV2026
Training-Free Object-Background Compositional T2I via Dynamic Spatial Guidance and Multi-Path Pruning
Yang Deng, David Mould, Paul L. Rosin +1
Existing text-to-image diffusion models, while excelling at subject synthesis, exhibit a persistent foreground bias that treats the background as a passive and under-optimized bypr…
cs.CV2026
MedLVR: Latent Visual Reasoning for Reliable Medical Visual Question Answering
Suyang Xi, Songtao Hu, Yuxiang Lai +4
Medical vision--language models (VLMs) have shown strong potential for medical visual question answering (VQA), yet their reasoning remains largely text-centric: images are encoded…