#natural language process...
May 2026
GraphLit: Learning Text-Enriched Dynamic Character Network Representations for Literary Study
Dynamic Heterogeneous Character Networks are introduced, which organize long novels into temporally localized heterogeneous graphs that align characters with their textual contexts, and GraphLit is proposed, a self-supervised learning framework that learns rich literary representations through a masked graph autoencoder objective.
Gaspard Michel, Elena V. Epure, Romain Hennequin et al.
· arXiv.org · 1 citation