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20212025
most citedTackling Morphological Analogies Using Deep Learning -- Extended Version

1 citations · 1 across the 4 of their papers we have counts for

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cs.CL2025

"Wait, did you mean the doctor?": Collecting a Dialogue Corpus for Topical Analysis

Amandine Decker, Vincent Tourneur, Maxime Amblard +1

Dialogue is at the core of human behaviour and being able to identify the topic at hand is crucial to take part in conversation. Yet, there are few accounts of the topical organisa…

cs.CL2024

With a Little Help from my (Linguistic) Friends: Topic Segmentation of Multi-party Casual Conversations

Amandine Decker, Maxime Amblard

Topics play an important role in the global organisation of a conversation as what is currently discussed constrains the possible contributions of the participant. Understanding th…

cs.CL2023

Topic and genre in dialogue

Amandine Decker, Ellen Breitholtz, Christine Howes +1

In this paper we argue that topic plays a fundamental role in conversations, and that the concept is needed in addition to that of genre to define interactions. In particular, the…

cs.CL20211 cited

Tackling Morphological Analogies Using Deep Learning -- Extended Version

Safa Alsaidi, Amandine Decker, Esteban Marquer +2

Analogical proportions are statements of the form "A is to B as C is to D". They constitute an inference tool that provides a logical framework to address learning, transfer, and e…

cs.CL2021

A Neural Approach for Detecting Morphological Analogies

Safa Alsaidi, Amandine Decker, Puthineath Lay +3

Analogical proportions are statements of the form "A is to B as C is to D" that are used for several reasoning and classification tasks in artificial intelligence and natural langu…

cs.CL2021

On the Transferability of Neural Models of Morphological Analogies

Safa Alsaidi, Amandine Decker, Puthineath Lay +3

Analogical proportions are statements expressed in the form "A is to B as C is to D" and are used for several reasoning and classification tasks in artificial intelligence and natu…