11 papers
Across the Loss Landscape with Progressive Growth
Paul Caillon, Christophe Cerisara, Alexandre Allauzen
Deep neural networks generalize well despite their highly nonconvex, overparameterized loss landscapes, a phenomenon often associated with the geometry of the minima found by stoch…
Benchmarking Generalization in Financial Statement Fraud Detection: robust evaluation and novel tasks
Guy Stephane Waffo Dzuyo, Gaël Guibon, Christophe Cerisara +1
Financial statement fraud detection (FSFD) is crucial for market integrity but faces challenges from increasingly sophisticated schemes and under-utilized textual data in financial…
Large Language Models for Citation Function Classification
Daniel VodiÄka, Jakub Å mÃd, Pavel Král +1
Citation function classification plays a crucial role in understanding the relationships between scientific publications and advancing bibliometric analysis. This study presents on…
GraphLit: Learning Text-Enriched Dynamic Character Network Representations for Literary Study
Gaspard Michel, Elena V. Epure, Romain Hennequin +2
Methods to represent literary texts as graphs or sequences of graphs mainly focus on representing character interactions, and often overlook another crucial aspect: the textual con…
Computational Narrative Understanding for Expressive Text-to-Speech
Gaspard Michel, Elena V. Epure, Christophe Cerisara
Recent advances in text-to-speech (TTS) have been driven by large, multi-domain speech corpora, yet the expressive potential of audiobook data remains underexamined. We argue that…
Cross-lingual Matryoshka Representation Learning across Speech and Text
Yaya Sy, Dioula Doucouré, Christophe Cerisara +1
Speakers of under-represented languages face both a language barrier, as most online knowledge is in a few dominant languages, and a modality barrier, since information is largely…