From the 1 of 17 linked papers with an AI index.
17 papers
ZUNA1.1: A more flexible EEG foundation model for Denoising and Super-resolution
Christopher Warner, Jonas Mago, JR Huml +1
The paper presents ZUNA1.1, a 380‑million‑parameter diffusion autoencoder that can denoise and super‑resolve EEG recordings of variable length and channel configurations, outperfor…
ZONOS2 Technical Report
Gabriel Clark, Sofian Mejjoute, Mohamed Osman +2
We present ZONOS2 8B, our latest TTS model, which achieves state-of-the-art naturalness, prosody, and voice cloning fidelity. We improve upon Zonos-v0.1 across scale, data, and tra…
Can Scale Save Us From Plasticity Loss in Large Language Models?
J. Fernando Hernandez-Garcia, Tomás Figliolia, Beren Millidge
The loss of plasticity - the ability of a network to learn new information after having already learned older information - is a fundamental challenge in creating artificial neural…
Scaling Adaptive Depth with Norm-Agnostic Residual Networks
Tomás Figliolia, Beren Millidge
Residual architectures are ubiquitous in deep learning, but they suffer from a subtle structural limitation: the norm of the residual stream can grow rapidly with depth. As a resul…
Zamba2-VL Technical Report
Hassan Shapourian, Kasra Hejazi, Olabode M. Sule +1
We present Zamba2-VL, a suite of vision-language models built on Zamba2, a hybrid language-model architecture combining Mamba2 state-space layers with a small number of shared tran…
Online Vector Quantized Attention
Nick Alonso, Tomas Figliolia, Beren Millidge
Standard sequence mixing layers used in language models struggle to balance efficiency and performance. Self-attention performs well on long context tasks but has expensive quadrat…