arXiv Machine Learning

IQ-JEPA: A Joint-Embedding Predictive Architecture with a Hermitian Vision Transformer for Sound Speed and Attenuation Estimation from Ultrasound IQ Data

arXiv:2607. 22351v1 Announce Type: new Abstract: The speed of sound in tissue is a prerequisite for well-focused imaging and has diagnostic value, but recovering it from raw pulse-echo channel data is fundamentally a nonlinear inverse problem.

arXiv Machine Learning

Aug 3

Few-shot Deep Learning for Phase-Amplitude Aberration Correction in Transcranial Focused Ultrasound

arXiv:2607. 29182v1 Announce Type: cross Abstract: Transcranial focused ultrasound (tFUS) is a non-invasive technique that delivers focused acoustic energy through the skull for neuromodulation and therapeutic applications.

By Minju Seol, Minjee Seo, Seonaeng Cho, Kyungho Yoon

fine-tuning safety

arXiv AI

Jul 21

SONAR: Spectral-Contrastive Audio Residuals for Generalizable Deepfake Detection

arXiv:2511. 21325v2 Announce Type: replace-cross Abstract: Deepfake (DF) audio detectors still struggle to generalize to out of distribution inputs.

By Ido Nitzan Hidekel, Gal lifshitz, Khen Cohen, Dan Raviv

rag diffusion benchmarks safety

arXiv Machine Learning

Jun 16

From Physics to Representation: Audio Learning with Synthetic Pre-training via Procedural Generation

arXiv:2606. 14791v1 Announce Type: cross Abstract: Self-supervised learning advances audio representation for multimedia analysis.

By Fengrui Liu, Ruiyang Huang, Qijian Zheng, Yuanfang Wang, Feng Liu

llms diffusion benchmarks safety

arXiv AI

Jul 23

PRIME-SVR: Physics-infoRmed Implicit Multi-Echo Slice-to-Volume Reconstruction for Fetal T2 mapping

arXiv:2607. 20136v1 Announce Type: cross Abstract: Slice-to-volume reconstruction (SVR) is the standard method for obtaining high-resolution (HR) 3D fetal brain volumes from motion-corrupted 2D MRI slice stacks acquired in multiple orientations.

By Busra Bulut, Maik Dannecker, Thomas Sanchez, Sara Neves Silva, Steven Jia, Jean-Baptiste Ledoux, Leo Pomar, Joanna Sichitiu, Yvan Gomez, Meriam Koob, Vincent Dunet, Maria Deprez, Guillaume Auzias, Francois Rousseau, Jana Hutter, Daniel Rueckert, Meritxell Bach Cuadra

benchmarks

arXiv AI

Jul 1

BEST-RQ-2: Contextualize-Then-Predict, a Two-Step Approach for Self-Supervised Audio Representations

arXiv:2606. 30700v1 Announce Type: cross Abstract: Self-supervised learning enables audio representations that transfer across domains and tasks.

By Ludovic K. Tuncay (IRIT-SAMoVA), Etienne Labb\'e (IRIT-SAMoVA), Thomas Pellegrini (IRIT-SAMoVA)

llms benchmarks

arXiv AI

Jun 10

FADA: Accessible fetal ultrasound interpretation and annotation with a selectively distilled unified vision-language model

arXiv:2606. 11106v1 Announce Type: cross Abstract: A global shortage of trained sonographers limits prenatal ultrasound screening in low- and middle-income countries, where over half of pregnant women receive no skilled sonography.

By Mahmood Alzubaidi, Uzair Shah, Raden Muaz, Ines Abbes, Nader Mohammed, Abdullatif Magram, Khalid Alyafei, Mowafa Househ, Marco Agus

llms agents computer-vision fine-tuning efficiency multimodal safety

arXiv Machine Learning

Jun 5

Boosting Brain-to-Image Decoding with TRIBE v2 Data Augmentation

arXiv:2606. 06345v1 Announce Type: cross Abstract: Brain decoding is limited by the availability of labeled neural data, and remains challenging in low-data regimes.

By Yohann Benchetrit, Marl\`ene Careil, Simon Dahan, Hubert Banville, St\'ephane d'Ascoli, Jean-R\'emi King

arXiv AI

Jul 22

FedCC: A Low-Resource Federated Adaptation of Foundation Models for Robust Corpus Callosum localization in Fetal Ultrasound Images

arXiv:2607. 18283v1 Announce Type: cross Abstract: Accurate localization of the corpus callosum (CC) in fetal ultrasound (US) images is crucial for the early identification of neurodevelopmental abnormalities.

By Alessandro Di Matteo, Sara Moccia, Giuseppe Rizzo, Gianpaolo Grisolia, Ricciarda Raffaelli, Lorenzo Vasciaveo, Francesco D'Antonio, Maria Chiara Fiorentino

computer-vision fine-tuning safety

arXiv Machine Learning

Jul 10

Structural Bottlenecks on Frequency Representation in End-to-End Audio Models

arXiv:2607. 08545v1 Announce Type: cross Abstract: End-to-end neural audio models achieve high-fidelity compression and generation.

By Nicole Cosme-Clifford

benchmarks safety

arXiv Machine Learning

Jul 21

A Framework for Early Sepsis Prediction via Self-Supervised (JEPA) and Federated Representation Learning

arXiv:2607. 16681v1 Announce Type: new Abstract: Early sepsis prediction from electronic health records is challenged by irregular sampling, high missingness, and class imbalance.

By Umair bin Mansoor, Munaf Rashid, Roomi Naqvi

rag fine-tuning efficiency benchmarks

arXiv Machine Learning

2d ago

Trajectory Dynamics in Self-Supervised Learning Latent Space for Audio Deepfake Detection

arXiv:2608. 13817v1 Announce Type: cross Abstract: Human speech production is constrained by physiology, giving rise to characteristic temporal structure on acoustic signals.

By Tom\'as Andrade Weber

diffusion benchmarks

arXiv AI

Jul 14

Encoder-Side Neuron Identification and Amplification for Acoustic Perception in Large Audio-Language Models

arXiv:2607. 11801v1 Announce Type: cross Abstract: Large audio-language models (LALMs) often underperform on fine-grained, non-semantic attributes of speech, such as a speaker's emotion, despite strong performance on speech content.

By Yu-Han Huang, Chih-Kai Yang, Ke-Han Lu, An-Yu Cheng, Hung-yi Lee

llms fine-tuning

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