activity
20162019
most citedRobust Semantic Parsing with Adversarial Learning for Domain Generalization

4 citations · 9 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL20193 cited

Adapting a FrameNet Semantic Parser for Spoken Language Understanding Using Adversarial Learning

Gabriel Marzinotto, Geraldine Damnati, Frédéric Béchet

This paper presents a new semantic frame parsing model, based on Berkeley FrameNet, adapted to process spoken documents in order to perform information extraction from broadcast co…

cs.CL20194 cited

Robust Semantic Parsing with Adversarial Learning for Domain Generalization

Gabriel Marzinotto, Geraldine Damnati, Frédéric Béchet +1

This paper addresses the issue of generalization for Semantic Parsing in an adversarial framework. Building models that are more robust to inter-document variability is crucial for…

cs.CL2019

Un duel probabiliste pour départager deux présidents (LIA @ DEFT'2005)

Marc El-Bèze, Juan-Manuel Torres-Moreno, Frédéric Béchet

We present a set of probabilistic models applied to binary classification as defined in the DEFT'05 challenge. The challenge consisted a mixture of two differents problems in Natur…

cs.CL20182 cited

Sources of Complexity in Semantic Frame Parsing for Information Extraction

Gabriel Marzinotto, Frédéric Béchet, Géraldine Damnati +1

This paper describes a Semantic Frame parsing System based on sequence labeling methods, precisely BiLSTM models with highway connections, for performing information extraction on…

cs.CL2018

FrameNet automatic analysis : a study on a French corpus of encyclopedic texts

Gabriel Marzinotto, Géraldine Damnati, Frederic Bechet

This article presents an automatic frame analysis system evaluated on a corpus of French encyclopedic history texts annotated according to the FrameNet formalism. The chosen approa…

cs.CL2018

Semantic Frame Parsing for Information Extraction : the CALOR corpus

Gabriel Marzinotto, Jeremy Auguste, Frederic Bechet +2

This paper presents a publicly available corpus of French encyclopedic history texts annotated according to the Berkeley FrameNet formalism. The main difference in our approach com…