Year: 2026

“They Really Clicked”: How do Multimodal LLMs Judge Rapport Between People?

Oussama Silem, Eric Villemonte de La Clergerie, Justine Cassell. “They Really Clicked”: How do Multimodal
LLMs Judge Rapport Between People?. Semdial 2026 – LuffDial, the 30th Workshop on the Semantics and
Pragmatics of Dialogue, Sep 2026, Loughborough, United Kingdom.

  • Conversation
  • MLLM
  • Multimodal
  • Rapport

Validation of a Multi-level Self-Report Rapport Scale and its Impact on Multimodal Modeling of Small Group Interaction

Justine Reverdy, Oussama Silem, and Justine Cassell. 2026. Validation of a Multi-level Self-Report Rapport Scale and its Impact on Multimodal Modeling of Small Group Interaction. In INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION (ICMI ’26), October 05–09, 2026, Napoli, Italy. ACM, New York, NY, USA, 15 pages. https://doi.org/10.1145/3776574.3831156

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  • Conversation
  • Machine Learning
  • Multimodal
  • Rapport

Using Machine Mental Imagery for Representing Common Ground in Situated Dialogue

Biswesh Mohapatra, Giovanni Duca, Laurent Romary, Justine Cassell. 2026. Using Machine Mental Imagery for Representing Common Ground in Situated Dialogue. Under Review.

  • Conversational Grounding
  • Machine Learning
  • Multimodal

Frame of Reference: Addressing the Challenges of Common Ground Representation in Situational Dialogs

Biswesh Mohapatra, Théo Charlot, Giovanni Duca, Mayank Palan, Laurent Romary, Justine Cassell. 2026. Frame of Reference: Addressing the Challenges of Common Ground Representation in Situational Dialogs. In Findings of the 202§ Conference on Association for Computational Linguistics:

  • Conversational Grounding
  • Evaluation
  • Machine Learning