Tootfinder

Factorized RVQ-GAN For Disentangled Speech Tokenization
Sameer Khurana, Dominik Klement, Antoine Laurent, Dominik Bobos, Juraj Novosad, Peter Gazdik, Ellen Zhang, Zili Huang, Amir Hussein, Ricard Marxer, Yoshiki Masuyama, Ryo Aihara, Chiori Hori, Francois G. Germain, Gordon Wichern, Jonathan Le Roux
https://arxiv.org/abs/2506.15…

Factorized RVQ-GAN For Disentangled Speech Tokenization
We propose Hierarchical Audio Codec (HAC), a unified neural speech codec that factorizes its bottleneck into three linguistic levels-acoustic, phonetic, and lexical-within a single model. HAC leverages two knowledge distillation objectives: one from a pre-trained speech encoder (HuBERT) for phoneme-level structure, and another from a text-based encoder (LaBSE) for lexical cues. Experiments on English and multilingual data show that HAC's factorized bottleneck yields disentangled token sets: one…

Researchers find evidence that a second fanpage.it journalist, along with an anonymous European journalist, were targeted using Graphite spyware (The Guardian)
https://www.theguardian.com/media/2025/jun/12/…

Distillation of atomistic foundation models across architectures and chemical domains
John L. A. Gardner, Daniel F. Thomas du Toit, Chiheb Ben Mahmoud, Zo\'e Faure Beaulieu, Veronika Juraskova, Laura-Bianca Pa\c{s}ca, Louise A. M. Rosset, Fernanda Duarte, Fausto Martelli, Chris J. Pickard, Volker L. Deringer
https://arxiv.or…

Distillation of atomistic foundation models across architectures and chemical domains
Machine-learned interatomic potentials have transformed computational research in the physical sciences. Recent atomistic `foundation' models have changed the field yet again: trained on many different chemical elements and domains, these potentials are widely applicable, but comparably slow and resource-intensive to run. Here we show how distillation via synthetic data can be used to cheaply transfer knowledge from atomistic foundation models to a range of different architectures, unlocking mu…

The Belfast News Letter, among the longest-running English dailies, digitizes and puts all its editions online, including the earliest surviving one from 1738 (Michael Savage/The Guardian)
https://www.theguardian.com/media/2025/jun/…