3 papers
cs.LG2025
Temporal horizons in forecasting: a performance-learnability trade-off
Pau Vilimelis Aceituno, Jack William Miller, Noah Marti +2
When training autoregressive models to forecast dynamical systems, a critical question arises: how far into the future should the model be trained to predict for optimal performanc…
cs.CL2025
CoPERLex: Content Planning with Event-based Representations for Legal Case Summarization
T. Y. S. S. Santosh, Youssef Farag, Matthias Grabmair
Legal professionals often struggle with lengthy judgments and require efficient summarization for quick comprehension. To address this challenge, we investigate the need for struct…
cs.CV2023
Urban-StyleGAN: Learning to Generate and Manipulate Images of Urban Scenes
George Eskandar, Youssef Farag, Tarun Yenamandra +3
A promise of Generative Adversarial Networks (GANs) is to provide cheap photorealistic data for training and validating AI models in autonomous driving. Despite their huge success,…