17 papers
Intent-Triggered Anchoring for Multi-Token Format Units in Parallel Decoding of Diffusion Language Models
Junhyeok Lee, Kyu Sung Choi
In parallel decoding, diffusion language models commit several tokens per forward pass, so co-committed tokens cannot see each other, breaking multi-token format units that parsers…
MC-CXR: A Multi-Context Chest X-ray Benchmark for Context-Induced Disruption in Vision-Language Models
Junhyeok Lee, Songsoo Kim, Kyu Sung Choi
Vision-language models (VLMs) are increasingly used in clinical pipelines where a chest X-ray is interpreted alongside retrieved reports, preliminary notes, or prior imaging. Exist…
Measured-Subspace Consistency: A Plug-and-Play Operator for Diffusion Posterior Sampling in Accelerated MRI Reconstruction
Junhyeok Lee, Kyu Sung Choi
Diffusion posterior samplers for accelerated MRI can reconstruct accurately yet still disagree on the acquired k-space across samples, placing posterior variability on coefficients…
TensorLDM: A Component-Wise Latent Diffusion Model for Volumetric DTI Reconstruction from Sparse DWIs
Junhyeok Lee, Kyu Sung Choi
Reconstructing diffusion tensors from sparse DWIs is critical for accelerating Diffusion Tensor Imaging (DTI) in clinical settings, yet current deep learning approaches frequently…
Spatio-Temporal Mixture-of-Modality-Experts Diffusion for Quantitative DCE-MRI Synthesis from Incomplete MR Sequences
Junhyeok Lee, Kyu Sung Choi
Quantitative maps from dynamic contrast-enhanced MRI (DCE-MRI) are essential for tumor assessment but are often unavailable due to contrast-agent risks and protocol variability. Pr…
MMed-Bench-IR: A Heterogeneous Benchmark for Multilingual Medical Information Retrieval
Junhyeok Lee, Han Jang, Hyeonjin Goh +1
Retrieval-augmented generation (RAG) in clinical settings increasingly requires multilingual retrieval against predominantly English evidence corpora. Multilingual medical retrieva…
MEDLAYXPLAIN: Benchmarking the Expert-Lay Gap in Medical Vision-Language Models
Han Jang, Junhyeok Lee, Songsoo Kim +4
Medical Vision-Language Models (Med-VLMs) achieve strong expert-level performance, yet their ability to generate patient-accessible descriptions remains underexplored. With the 21s…
Hierarchical Perfusion Graphs for Tumor Heterogeneity Modeling in Glioma Molecular Subtyping
Han Jang, Junhyeok Lee, Heeseong Eum +4
Precise molecular subtyping of gliomas, including isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion, directly guides surgical and therapeutic decisions, yet currently r…
Perturbative Nicolai-Map Diagrammatics: Application to Poincaré Supergravity
Ji-Seong Chae, Hun Jang, Junhyeok Lee
We develop a perturbative, diagrammatic framework for constructing Nicolai maps and apply it to four-dimensional Poincaré supergravity expanded around flat Minkowsk…
MedLayBench-V: A Large-Scale Benchmark for Expert-Lay Semantic Alignment in Medical Vision Language Models
Han Jang, Junhyeok Lee, Heeseong Eum +1
Medical Vision-Language Models (Med-VLMs) have achieved expert-level proficiency in interpreting diagnostic imaging. However, current models are predominantly trained on profession…
Segmentation-before-Staining Improves Structural Fidelity in Virtual IHC-to-Multiplex IF Translation
Junhyeok Lee, Han Jang, Heeseong Eum +2
Multiplex immunofluorescence (mIF) enables simultaneous single-cell quantification of multiple biomarkers within intact tissue architecture, yet its high reagent cost, multi-round…
SciZoom: A Large-scale Benchmark for Hierarchical Scientific Summarization across the LLM Era
Han Jang, Junhyeok Lee, Kyu Sung Choi
The explosive growth of AI research has created unprecedented information overload, increasing the demand for scientific summarization at multiple levels of granularity beyond trad…
Evidential Perfusion Physics-Informed Neural Networks with Residual Uncertainty Quantification
Junhyeok Lee, Minseo Choi, Han Jang +5
Physics-informed neural networks (PINNs) have shown promise in addressing the ill-posed deconvolution problem in computed tomography perfusion (CTP) imaging for acute ischemic stro…
MPIB: A Benchmark for Medical Prompt Injection Attacks and Clinical Safety in LLMs
Junhyeok Lee, Han Jang, Kyu Sung Choi
Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems are increasingly integrated into clinical workflows. However, prompt injection attacks can steer these…
Lesion-Aware Post-Training of Latent Diffusion Models for Synthesizing Diffusion MRI from CT Perfusion
Junhyeok Lee, Hyunwoong Kim, Hyungjin Chung +4
Image-to-Image translation models can help mitigate various challenges inherent to medical image acquisition. Latent diffusion models (LDMs) leverage efficient learning in compress…
Domain-Specialized Interactive Segmentation Framework for Meningioma Radiotherapy Planning
Junhyeok Lee, Han Jang, Kyu Sung Choi
Precise delineation of meningiomas is crucial for effective radiotherapy (RT) planning, directly influencing treatment efficacy and preservation of adjacent healthy tissues. While…
Improving Factuality of 3D Brain MRI Report Generation with Paired Image-domain Retrieval and Text-domain Augmentation
Junhyeok Lee, Yujin Oh, Dahyoun Lee +9
Acute ischemic stroke (AIS) requires time-critical decision-making, where inaccurate interpretation of neuroimaging findings can lead to irreversible disability. Diffusion-weighted…