Adjustment for Confounding using Pre-Trained Representations
arXiv:2506.14329v1 Announce Type: cross Abstract: There is growing interest in extending average treatment effect (ATE) estimation to incorporate non-tabular data,…
Graph-Convolutional-Beta-VAE for Synthetic Abdominal Aorta Aneurysm Generation
arXiv:2506.13628v2 Announce Type: replace-cross Abstract: Synthetic data generation plays a crucial role in medical research by mitigating privacy concerns and…
sHGCN: Simplified hyperbolic graph convolutional neural networks
arXiv:2506.14438v1 Announce Type: cross Abstract: Hyperbolic geometry has emerged as a powerful tool for modeling complex, structured data, particularly where…
Unifying Streaming and Non-streaming Zipformer-based ASR
arXiv:2506.14434v1 Announce Type: cross Abstract: There has been increasing interest in unifying streaming and non-streaming automatic speech recognition (ASR) models…
Next-generation phenotyping of inherited retinal diseases from multimodal imaging with Eye2Gene
Nature Machine Intelligence, Published online: 18 June 2025; doi:10.1038/s42256-025-01040-8 Eye2Gene’s next-generation phenotyping of multimodal images increases diagnostic yield for inherited…
A Synthetic Pseudo-Autoencoder Invites Examination of Tacit Assumptions in Neural Network Design
arXiv:2506.12076v1 Announce Type: cross Abstract: We present a handcrafted neural network that, without training, solves the seemingly difficult problem of…
MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks
arXiv:2506.07016v2 Announce Type: replace-cross Abstract: Large multimodal models (LMMs) have shown remarkable progress in audio-visual understanding, yet they struggle with…
Autonomous Computer Vision Development with Agentic AI
arXiv:2506.11140v2 Announce Type: replace-cross Abstract: Agentic Artificial Intelligence (AI) systems leveraging Large Language Models (LLMs) exhibit significant potential for complex…
ZINA: Multimodal Fine-grained Hallucination Detection and Editing
arXiv:2506.13130v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) often generate hallucinations, where the output deviates from the visual…