most citedRobust Semantic Parsing with Adversarial Learning for Domain Generalization

4 citations · 10 across the 5 of their papers we have counts for

collaborators

6 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.CL20191 cited

MaskParse@Deskin at SemEval-2019 Task 1: Cross-lingual UCCA Semantic Parsing using Recursive Masked Sequence Tagging

Gabriel Marzinotto, Johannes Heinecke, Geraldine Damnati

This paper describes our recursive system for SemEval-2019 \textit{ Task 1: Cross-lingual Semantic Parsing with UCCA}. Each recursive step consists of two parts. We first perform s…

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.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…