Latest AI and machine learning research in surveys for healthcare professionals.
Recent research has shown that text-to-image diffusion models are capable of generating high-quality images guided by text prompts. But can they be used to generate or approximate real-world images from the seed noise? This is known as the diffusion inversion problem, which serves as a fundamental building block for bridging diffusion models and real-world scenarios. However, existing diffusion in...
RLHF-aligned language models exhibit response homogenization: on TruthfulQA (n=790), 40-79% of questions produce a single semantic cluster across 10 i.i.d. samples. On affected questions, sampling-based uncertainty methods have zero discriminative power (AUROC=0.500), while free token entropy retains signal (0.603). This alignment tax is task-dependent: on GSM8K (n=500), token entropy achieves 0.7...
Rapid and accurate structural damage assessment following natural disasters is critical for effective emergency response and recovery. However, remote...
Consistency under paraphrase, the property that semantically equivalent prompts yield identical predictions, is increasingly used as a proxy for relia...
Transformer-based Genomic Language Models (GLMs) have achieved strong performance across diverse genomic prediction tasks. However, their tendency tow...
Collecting and annotating datasets for pixel-level semantic segmentation tasks are highly labor-intensive. Data augmentation provides a viable solutio...
When working with real-world insurance data, practitioners often encounter challenges during the data preparation stage that can undermine the statist...
Generative models are widely used to compensate for class imbalance in AI training pipelines, yet their failure modes under low-data conditions are po...
Vision-language process reward models (VL-PRMs) are increasingly used to score intermediate reasoning steps and rerank candidates under test-time scal...
Lung cancer is a condition where there is abnormal growth of malignant cells that spread in an uncontrollable fashion in the lungs. Some common treatm...
Real-time tracking and automated response systems are essential for standardising experiments, reducing observer bias, and improving reproducibility i...
Mental health related problems in adolescents are not always properly evaluated because of incomplete evaluation methods that do not combine biologica...
Machine learning models deployed in critical care settings exhibit demographic biases, particularly gender disparities, that undermine clinical trust ...
Artificial intelligence (AI)-driven decision support systems can improve diagnostic accuracy and efficiency in computational pathology. However, colla...
Weakly Supervised Object Localization (WSOL) models enable joint classification and region-of-interest localization in histology images using only ima...
Background: Longitudinal measurement of depression severity in outpatient psychiatric care is limited by infrequent standardized assessments. Although...
Recent advances in learning-based robot manipulation have produced policies with remarkable capabilities. Yet, reliability at deployment remains a fun...
Many operational AI systems depend on large-scale human annotation to detect rare but consequential events (e.g., fraud, defects, and medical abnormal...
Artificial intelligence (AI)-driven decision support systems can improve diagnostic accuracy and efficiency in computational pathology. However, colla...
Understanding how neural networks rely on visual cues offers a human-interpretable view of their internal decision processes. The cue-conflict benchma...