6 citations · 10 across the 9 of their papers we have counts for
17 papers
Graph Neural Network Policies and Imitation Learning for Multi-Domain Task-Oriented Dialogues
Thibault Cordier, Tanguy Urvoy, Fabrice Lefèvre +1
Task-oriented dialogue systems are designed to achieve specific goals while conversing with humans. In practice, they may have to handle simultaneously several domains and tasks. T…
Hyperbolic Temporal Knowledge Graph Embeddings with Relational and Time Curvatures
Sebastien Montella, Lina Rojas-Barahona, Johannes Heinecke
Knowledge Graph (KG) completion has been excessively studied with a massive number of models proposed for the Link Prediction (LP) task. The main limitation of such models is their…
Is the User Enjoying the Conversation? A Case Study on the Impact on the Reward Function
Lina M. Rojas-Barahona
The impact of user satisfaction in policy learning task-oriented dialogue systems has long been a subject of research interest. Most current models for estimating the user satisfac…
Denoising Pre-Training and Data Augmentation Strategies for Enhanced RDF Verbalization with Transformers
Sebastien Montella, Betty Fabre, Tanguy Urvoy +2
The task of verbalization of RDF triples has known a growth in popularity due to the rising ubiquity of Knowledge Bases (KBs). The formalism of RDF triples is a simple and efficien…
Diluted Near-Optimal Expert Demonstrations for Guiding Dialogue Stochastic Policy Optimisation
Thibault Cordier, Tanguy Urvoy, Lina M. Rojas-Barahona +1
A learning dialogue agent can infer its behaviour from interactions with the users. These interactions can be taken from either human-to-human or human-machine conversations. Howev…
Spoken Conversational Search for General Knowledge
Lina M. Rojas-Barahona, Pascal Bellec, Benoit Besset +8
We present a spoken conversational question answering proof of concept that is able to answer questions about general knowledge from Wikidata. The dialogue component does not only…