• HDR Defended on :
  • Nov 17, 2022 • salle des thèses, Faculté des sciences Jean Perrin


My habilitation provides a high-level overview of my contributions on inducing commonsense knowledge using vector space representations, with a focus on :

  • Learning conceptual space representations (learning entity embeddings and region-based representations of concepts, learning interpretable dimensions)
  • Modelling relational knowledge (relation induction in word embedding and pre-trained language models, learning of distributional relation vectors)
  • Deriving high quality vectors from contextualised LMs and applications to few-shot learning.
  • Plausible reasoning about ontologies (automated rule base completion, inconsistency handling and belief merging)


  • Isabelle Bloch (Sorbonne Université)
  • Jesse Davis (KU Leuven)
  • Philippe Langlais (Université de Montréal)
  • Daniel Le Berre (Université d’Artois)
  • Henri Prade (IRIT Toulouse)
  • Marie-Christine Rousset (Université Grenoble Alpes)
  • Steven Schockaert (Cardiff University)