Latest AI and machine learning research in schizophrenia for healthcare professionals.
Synthetic data is widely used in healthcare to create datasets that are similar to original data but...
Multimodal large language models (MLLMs) have become a key interface for visual reasoning and ground...
Randomized neural networks (RdNNs) enable efficient, backpropagation-free training by freezing rando...
Foundation diffusion models can generate photorealistic natural images, but adapting them to medical...
Large vision-language models (VLMs) demonstrate strong performance in medical image understanding, b...
Large language models are increasingly deployed in clinical decision-support contexts, yet systemati...
Despite the breakneck pace of progress in protein design methodology, frontier problems remain chall...
Ground-to-space astronomical super-resolution requires recovering space-quality images from ground-b...
Large Vision-Language Models (LVLMs) often suffer from hallucinations, generating descriptions that ...
Text-to-Image generation has seen significant advancements in output realism with the advent of diff...
Linear models are widely used in computational neuroimaging to identify biomarkers associated with b...
Hallucinations in Speech Large Language Models (SpeechLLMs) pose significant risks, yet existing det...
Recent advances in Vision-Language Models (VLMs) have substantially enhanced their ability across mu...
Latent diffusion models for medical image super-resolution universally inherit variational autoencod...
Accurately detecting and localizing hallucinations is a critical task for ensuring high reliability ...
Vision-Language Models (VLMs) excel at multimodal tasks, but they remain vulnerable to hallucination...
As vision-language models (VLMs) are increasingly deployed in clinical decision support, more than a...
Transfer learning (TL) and deep ensemble learning (DE) have recently been shown to outperform simple...
The deployment of large language models (LLMs) for science carries an intrinsic risk: hallucination ...
Accurate prediction of drug-target binding affinity across multiple pharmacological endpoints remain...
Accurate uncertainty quantification is crucial for making reliable decisions in various supervised l...