3 papers
cs.LG2026
Latent States in Neural Networks: Recovering the Temporal Structure of Drifting Data from Model Weights
Kevin Guan
A temporally drifting data stream may pass through discrete regimes rather than changing continuously. We ask whether such regimes are recoverable from the weights of models traine…
cs.CL2026
AfriSUD: A Dependency Treebank Collection for Evaluating Models on African Languages
Happy Buzaaba, Cheikh Mouhamadou Bamba Dione, David Ifeoluwa Adelani +15
Despite their linguistic diversity and global significance, African languages remain underrepresented in research and resources to support NLP. We aim to bridge this gap by introdu…
cs.CL2026
Dependency Parsing Across the Resource Spectrum: Evaluating Architectures on High and Low-Resource Languages
Kevin Guan, Happy Buzaaba, Christiane Fellbaum
Transformer-based models achieve state-of-the-art dependency parsing for high-resource languages, yet their advantage over simpler architectures in low-resource settings remains po…