Offre en lien avec l’Action/le Réseau : – — –/– — –

Laboratoire/Entreprise : LIFAT & LIFO
Durée : 3 ans
Contact : alexandre.chanson@univ-tours.fr
Date limite de publication : 2025-05-12

Contexte :
In the era of data-driven decision-making, extracting insights from large datasets is crucial. Data narration refers to transforming data insights into interactive visual stories to enhance understanding and communication. While recent advances in AI and LLMs have introduced automation in data exploration and storytelling, challenges remain in personalization, user intent recognition, and interactive data narration.

*** Detailed subject attached ***

Sujet :
Key Research Questions :

– User Intent & Interaction: How can user preferences and feedback guide LLM-driven data storytelling?
– Personalization: How can data stories be adapted to different audience profiles, knowledge levels, and presentation styles?
– Exploration-Narration Interplay: How can data exploration and storytelling be seamlessly integrated to allow iterative user intervention?
– Quality Assessment: How can we evaluate and benchmark the effectiveness of generated data stories?

The candidate is expected to contribute to one of the first three research questions while considering the fourth as a transversal aspect.

*** Detailed subject attached ***

Profil du candidat :
Master’s degree in Computer Science :
– Strong background in databases and machine learning
– Interest in data exploration, storytelling, or NLP

Formation et compétences requises :
— Application Deadline: May 12, 2025 —
To apply, please email the following documents to the supervisors:
– CV
– Master’s transcripts
– Cover letter
– Reference letters, if any

Adresse d’emploi :
Université de Tours site de Blois

Document attaché : 202502191608_phd-llm-storytelling.pdf