collaborators

8 papers

cs.CV2026

MedProbeBench: Systematic Benchmarking at Deep Evidence Integration for Expert-level Medical Guideline

Jiyao Liu, Jianghan Shen, Sida Song +19

Recent advances in deep research systems enable large language models to retrieve, synthesize, and reason over large-scale external knowledge. In medicine, developing clinical guid…

cs.CV2026

MedQ-Engine: A Closed-Loop Data Engine for Evolving MLLMs in Medical Image Quality Assessment

Jiyao Liu, Junzhi Ning, Wanying Qu +4

Medical image quality assessment (Med-IQA) is a prerequisite for clinical AI deployment, yet multimodal large language models (MLLMs) still fall substantially short of human expert…

cs.CV2026

MedQ-UNI: Toward Unified Medical Image Quality Assessment and Restoration via Vision-Language Modeling

Jiyao Liu, Junzhi Ning, Wanying Qu +4

Existing medical image restoration (Med-IR) methods are typically modality-specific or degradation-specific, failing to generalize across the heterogeneous degradations encountered…

eess.IV2026

Open World MRI Reconstruction with Bias-Calibrated Adaptation

Jiyao Liu, Shangqi Gao, Lihao Liu +5

Real-world MRI reconstruction systems face the open-world challenge: test data from unseen imaging centers, anatomical structures, or acquisition protocols can differ drastically f…

cs.CV2026

MedQ-Deg: A Multidimensional Benchmark for Evaluating MLLMs Across Medical Image Quality Degradations

Jiyao Liu, Junzhi Ning, Chenglong Ma +14

Despite impressive performance on standard benchmarks, multimodal large language models (MLLMs) face critical challenges in real-world clinical environments where medical images in…

cs.CV2025

GOOD: Training-Free Guided Diffusion Sampling for Out-of-Distribution Detection

Xin Gao, Jiyao Liu, Guanghao Li +8

Recent advancements have explored text-to-image diffusion models for synthesizing out-of-distribution (OOD) samples, substantially enhancing the performance of OOD detection. Howev…