arXiv:2607. 17232v1 Announce Type: cross Abstract: Classical rate-distortion (RD) theory has long established the fundamental limits of lossy compression by quantifying the minimum number of bits required to represent a source under a prescribed distortion constraint.
By Photios A. Stavrou, Giuseppe Serra, Marios Kountouris
arXiv:2608. 16696v1 Announce Type: cross Abstract: Physical AI systems such as autonomous vehicles and robots rely on timely exchange of high-dimensional sensory signals under tight bandwidth, latency, and energy budgets.
By Homa Esfahanizadeh, Matin Mortaheb, Jinfeng Du, Harish Viswanathan
arXiv:2604. 14603v2 Announce Type: replace-cross Abstract: The fundamental limit of natural signal compression has traditionally been characterized by classical rate-distortion (RD) theory through the tradeoff between coding rate and reconstruction distortion, while the rate-distortion-perception (RDP) framework introduces a divergence-based measure of perceptual quality as a modeling principle, leaving its theoretical origin unclear.
By Zijian Liang, Kai Niu, Changshuo Wang, Jin Xu, Ping Zhang
arXiv:2512. 11000v2 Announce Type: replace-cross Abstract: Representations pervade our daily experience, from letters representing sounds to bit strings encoding digital files.
By Francesco L\"assig
arXiv:2607. 15693v1 Announce Type: cross Abstract: We describe a model of perceptual inference in primary visual cortex (V1) equivalent to a minimal diffusion model whose function can be readily understood from its parameters.
By Zeyu Yun, Alexander Belsten, Dasheng Bi, Zahra Kadkhodaie, Yubei Chen, Bruno A. Olshausen
arXiv:2511. 02496v2 Announce Type: replace Abstract: We study latent geometry as an explicit component of representation quality in data-scarce learning.
By Ronald Katende