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

Biswesh Mohapatra, Théo Charlot, Giovanni Duca, Mayank Palan, Laurent Romary +1 more
1/14/2026
cs.CLcs.AI

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Abstract

Common ground plays a critical role in situated spoken dialogues, where interlocutors must establish and maintain shared references to entities, events, and relations to sustain coherent interaction. For dialog systems, the ability to correctly ground conversational content in order to refer back to it later is particularly important. Prior studies have demonstrated that LLMs are capable of performing grounding acts such as requesting clarification or producing acknowledgments, yet relatively little work has investigated how common ground can be explicitly represented and stored for later use. Without such mechanisms, it remains unclear whether acknowledgment or clarification behaviors truly reflect a grounded understanding. In this work, we evaluate a model's ability to establish and exploit common ground through relational references to entities within the shared context in a situational dialogue. We test multiple methods for representing common ground in situated dialogues and further propose approaches to improve both the establishment of common ground and its subsequent use in the conversation.

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Cite this paper

@article{mohapatra2026frame,
  title  = {Frame of Reference: Addressing the Challenges of Common Ground Representation in Situational Dialogs},
  author = {Biswesh Mohapatra and Théo Charlot and Giovanni Duca and Mayank Palan and Laurent Romary and Justine Cassell},
  year   = {2026},
  eprint = {2601.09365},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2601.09365v1}
}

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