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Found 15 papers, 2 papers with code
Investigation par m\'ethodes d'apprentissage des sp\'ecificit\'es langagi\`eres propres aux personnes avec schizophr\'enie (Investigating Learning Methods Applied to Language Specificity of Persons with Schizophrenia)
Nous pr{\'e}sentons des exp{\'e}riences visant {\`a} identifier automatiquement des patients pr{\'e}sentant des sympt{\^o}mes de schizophr{\'e}nie dans des conversations contr{\^o}l{\'e}es entre patients et psychoth{\'e}rapeutes.
Which aspects of discourse relations are hard to learn? Primitive decomposition for discourse relation classification
Discourse relation classification has proven to be a hard task, with rather low performance on several corpora that notably differ on the relation set they use.
Aligning Discourse and Argumentation Structures using Subtrees and Redescription Mining
In this paper, we investigate similarities between discourse and argumentation structures by aligning subtrees in a corpus containing both annotations.
EusDisParser: improving an under-resourced discourse parser with cross-lingual data
More precisely, we build a monolingual system using the small set of data available and investigate the use of multilingual word embeddings to train a system for Basque using data annotated for another language.
ToNy: Contextual embeddings for accurate multilingual discourse segmentation of full documents
Segmentation is the first step in building practical discourse parsers, and is often neglected in discourse parsing studies.
When does deep multi-task learning work for loosely related document classification tasks?
This work aims to contribute to our understanding of \textit{when} multi-task learning through parameter sharing in deep neural networks leads to improvements over single-task learning.
Does syntax help discourse segmentation? Not so much
Discourse segmentation is the first step in building discourse parsers.
Is writing style predictive of scientific fraud?
The problem of detecting scientific fraud using machine learning was recently introduced, with initial, positive results from a model taking into account various general indicators.
Cross-lingual and cross-domain discourse segmentation of entire documents
Discourse segmentation is a crucial step in building end-to-end discourse parsers.
Multi-view and multi-task training of RST discourse parsers
We experiment with different ways of training LSTM networks to predict RST discourse trees.
Ranked #10 on
Discourse Parsing
on RST-DT
