16 citations · 24 across the 28 of their papers we have counts for
3 papers · 1 filter
Spend Bits Where Queries Look: KV Cache Vector Quantization with Attention-Preserving Transforms
Samuel Fernández-Menduiña, Amir Ziashahabi, Eduardo Pavez +2
Long-context LLM decoding reads the key-value (KV) cache at every step. Loading it takes longer than computing attention over it, so throughput is bandwidth-bound. Hence, reducing…
L2G-Net: Local to Global Spectral Graph Neural Networks via Cauchy Factorizations
Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega
Despite their theoretical advantages, spectral methods based on the graph Fourier transform (GFT) are seldom used in graph neural networks (GNNs) due to the cost of computing the e…
Towards joint graph learning and sampling set selection from data
Shashank N. Sridhara, Eduardo Pavez, Antonio Ortega
We explore the problem of sampling graph signals in scenarios where the graph structure is not predefined and must be inferred from data. In this scenario, existing approaches rely…