Tootfinder

SeFEF: A Seizure Forecasting Evaluation Framework
Ana Sofia Carmo, Louren\c{c}o Abrunhosa Rodrigues, Ana Rita Peralta, Ana Fred, Carla Bentes, Hugo Pl\'acido da Silva
https://arxiv.org/abs/2510.11275

SeFEF: A Seizure Forecasting Evaluation Framework
The lack of standardization in seizure forecasting slows progress in the field and limits the clinical translation of forecasting models. In this work, we introduce a Python-based framework aimed at streamlining the development, assessment, and documentation of individualized seizure forecasting algorithms. The framework automates data labeling, cross-validation splitting, forecast post-processing, performance evaluation, and reporting. It supports various forecasting horizons and includes a …

VersionRAG: Version-Aware Retrieval-Augmented Generation for Evolving Documents
Daniel Huwiler, Kurt Stockinger, Jonathan F\"urst
https://arxiv.org/abs/2510.08109 https://

VersionRAG: Version-Aware Retrieval-Augmented Generation for Evolving Documents
Retrieval-Augmented Generation (RAG) systems fail when documents evolve through versioning-a ubiquitous characteristic of technical documentation. Existing approaches achieve only 58-64% accuracy on version-sensitive questions, retrieving semantically similar content without temporal validity checks. We present VersionRAG, a version-aware RAG framework that explicitly models document evolution through a hierarchical graph structure capturing version sequences, content boundaries, and changes be…