3 citations · 6 across the 6 of their papers we have counts for
6 papers
Persistent Homology of Topic Networks for the Prediction of Reader Curiosity
Manuel D. S. Hopp, Vincent Labatut, Arthur Amalvy +4
Reader curiosity, the drive to seek information, is crucial for textual engagement, yet remains relatively underexplored in NLP. Building on Loewenstein's Information Gap Theory, w…
Conversation-Based Multimodal Abuse Detection Through Text and Graph Embeddings
Noé Cecillon, Vincent Labatut, Richard Dufour
Abusive behavior is common on online social networks, and forces the hosts of such platforms to find new solutions to address this problem. Various methods have been proposed to au…
The Role of Natural Language Processing Tasks in Automatic Literary Character Network Construction
Arthur Amalvy, Vincent Labatut, Richard Dufour
The automatic extraction of character networks from literary texts is generally carried out using natural language processing (NLP) cascading pipelines. While this approach is wide…
Whole-Graph Representation Learning For the Classification of Signed Networks
Noé Cecillon, Vincent Labatut, Richard Dufour +1
Graphs are ubiquitous for modeling complex systems involving structured data and relationships. Consequently, graph representation learning, which aims to automatically learn low-d…
Renard: A Modular Pipeline for Extracting Character Networks from Narrative Texts
Arthur Amalvy, Vincent Labatut, Richard Dufour
Renard (Relationships Extraction from NARrative Documents) is a Python library that allows users to define custom natural language processing (NLP) pipelines to extract character n…
Learning to Rank Context for Named Entity Recognition Using a Synthetic Dataset
Arthur Amalvy, Vincent Labatut, Richard Dufour
While recent pre-trained transformer-based models can perform named entity recognition (NER) with great accuracy, their limited range remains an issue when applied to long document…