1 citations · 3 across the 12 of their papers we have counts for
14 papers
Discourse Structure Extraction from Pre-Trained and Fine-Tuned Language Models in Dialogues
Chuyuan Li, Patrick Huber, Wen Xiao +3
Discourse processing suffers from data sparsity, especially for dialogues. As a result, we explore approaches to build discourse structures for dialogues, based on attention matric…
How much of UCCA can be predicted from AMR?
Siyana Pavlova, Maxime Amblard, Bruno Guillaume
In this paper, we consider two of the currently popular semantic frameworks: Abstract Meaning Representation (AMR)a more abstract framework, and Universal Conceptual Cognitive Anno…
Graph Querying for Semantic Annotations
Maxime Amblard, Bruno Guillaume, Siyana Pavlova +1
This paper presents how the online tool GREW-MATCH can be used to make queries and visualise data from existing semantically annotated corpora. A dedicated syntax is available to c…
A Multi-Party Dialogue Ressource in French
Maria Boritchev, Maxime Amblard
We present Dialogues in Games (DinG), a corpus of manual transcriptions of real-life, oral, spontaneous multi-party dialogues between French-speaking players of the board game Cata…
Multi-Task Learning for Depression Detection in Dialogs
Chuyuan Li, Chloé Braud, Maxime Amblard
Depression is a serious mental illness that impacts the way people communicate, especially through their emotions, and, allegedly, the way they interact with others. This work exam…
Reducing Unintended Bias of ML Models on Tabular and Textual Data
Guilherme Alves, Maxime Amblard, Fabien Bernier +2
Unintended biases in machine learning (ML) models are among the major concerns that must be addressed to maintain public trust in ML. In this paper, we address process fairness of…