Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 47,591 to 47,600 of 224,199 articles

Provably Safe Generative Sampling with Constricting Barrier Functions

arXiv
Flow-based generative models, such as diffusion models and flow matching models, have achieved remarkable success in learning complex data distributions. However, a critical gap remains for their deployment in safety-critical domains: the lack of for... read more 

Causal Decoding for Hallucination-Resistant Multimodal Large Language Models

arXiv
Multimodal Large Language Models (MLLMs) deliver detailed responses on vision-language tasks, yet remain susceptible to object hallucination (introducing objects not present in the image), undermining reliability in practice. Prior efforts often rely... read more 

Olbedo: An Albedo and Shading Aerial Dataset for Large-Scale Outdoor Environments

arXiv
Intrinsic image decomposition (IID) of outdoor scenes is crucial for relighting, editing, and understanding large-scale environments, but progress has been limited by the lack of real-world datasets with reliable albedo and shading supervision. We in... read more 

Imputation of Unknown Missingness in Sparse Electronic Health Records

arXiv
Machine learning holds great promise for advancing the field of medicine, with electronic health records (EHRs) serving as a primary data source. However, EHRs are often sparse and contain missing data due to various challenges and limitations in dat... read more 

SceMoS: Scene-Aware 3D Human Motion Synthesis by Planning with Geometry-Grounded Tokens

arXiv
Synthesizing text-driven 3D human motion within realistic scenes requires learning both semantic intent ("walk to the couch") and physical feasibility (e.g., avoiding collisions). Current methods use generative frameworks that simultaneously learn hi... read more 

LESA: Learnable Stage-Aware Predictors for Diffusion Model Acceleration

arXiv
Diffusion models have achieved remarkable success in image and video generation tasks. However, the high computational demands of Diffusion Transformers (DiTs) pose a significant challenge to their practical deployment. While feature caching is a pro... read more 

Strategy-Supervised Autonomous Laparoscopic Camera Control via Event-Driven Graph Mining

arXiv
Autonomous laparoscopic camera control must maintain a stable and safe surgical view under rapid tool-tissue interactions while remaining interpretable to surgeons. We present a strategy-grounded framework that couples high-level vision-language infe... read more 

Leveraging Causal Reasoning Method for Explaining Medical Image Segmentation Models

arXiv
Medical image segmentation plays a vital role in clinical decision-making, enabling precise localization of lesions and guiding interventions. Despite significant advances in segmentation accuracy, the black-box nature of most deep models has raised ... read more 

How Do Inpainting Artifacts Propagate to Language?

arXiv
We study how visual artifacts introduced by diffusion-based inpainting affect language generation in vision-language models. We use a two-stage diagnostic setup in which masked image regions are reconstructed and then provided to captioning models, e... read more 

Towards Secure and Efficient DNN Accelerators via Hardware-Software Co-Design

arXiv
The rapid deployment of deep neural network (DNN) accelerators in safety-critical domains such as autonomous vehicles, healthcare systems, and financial infrastructure necessitates robust mechanisms to safeguard data confidentiality and computational... read more