# A Formal Analysis of Multimodal Referring Strategies Under Common Ground

arXiv: https://arxiv.org/abs/2003.07385 · HTML: https://mlsanity.com/paper/2003.07385/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Mar 2020.

## Built on by (most cited first, 5 of 5)

- [Common Ground Tracking in Multimodal Dialogue](https://mlsanity.com/paper/2403.17284/) (2024)
- [TRACE: Real-Time Multimodal Common Ground Tracking in Situated Collaborative Dialogues](https://mlsanity.com/paper/2503.09511/) (2025)
- [NatSGD: A Dataset with Speech, Gestures, and Demonstrations for Robot Learning in Natural Human-Robot Interaction](https://mlsanity.com/paper/2403.02274/) (2024)
- [Dynamic Epistemic Friction in Dialogue](https://mlsanity.com/paper/2506.10934/) (2025)
- [Distributed Partial Information Puzzles: Examining Common Ground Construction Under Epistemic Asymmetry](https://mlsanity.com/paper/2603.05450/) (2026)

## Abstract (arXiv)

In this paper, we present an analysis of computationally generated mixed-modality definite referring expressions using combinations of gesture and linguistic descriptions. In doing so, we expose some striking formal semantic properties of the interactions between gesture and language, conditioned on the introduction of content into the common ground between the (computational) speaker and (human) viewer, and demonstrate how these formal features can contribute to training better models to predict viewer judgment of referring expressions, and potentially to the generation of more natural and informative referring expressions.