Skip to content

Author

Gaspard Michel

1 paper indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

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. · 1 citation

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.