Papers by Luc Lamontagne

2 papers
A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as Well (2020.lrec-1)

Copied to clipboard

Challenge: Existing methods for fully unsupervised cross-lingual mapping of word embeddings are available to achieve such a mapping .
Approach: They reproduce the experiments of Artetxe and Sgaard (2018) . they propose a robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings.
Outcome: The proposed method is feasible with minor assumptions, and it is able to be replicated in four languages.
SMARTR: A Framework for Early Detection using Survival Analysis of Longitudinal Texts (2024.naacl-srw)

Copied to clipboard

Challenge: a paper aims to detect expensive insurance claims early using textual information from claims notes.
Approach: They propose a model that leverages survival analysis concepts from claims notes to enhance a posteriori classification and early detection.
Outcome: The proposed model improves classification and early detection without reducing performance . it is based on a privately held corpus of claim files from a Canadian insurer .

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations