# Grounded Agreement Games: Emphasizing Conversational Grounding in Visual Dialogue Settings

arXiv: https://arxiv.org/abs/1908.11279 · HTML: https://mlsanity.com/paper/1908.11279/

## Key facts

- Cited by 10 papers in the map (data through 7 Oct 2026).
- First posted on arXiv 29 Aug 2019.

## Built on by (most cited first, 10 of 10)

- [Decision-Oriented Dialogue for Human-AI Collaboration](https://mlsanity.com/paper/2305.20076/) (2023)
- [Dialogue Games for Benchmarking Language Understanding: Motivation, Taxonomy, Strategy](https://mlsanity.com/paper/2304.07007/) (2023)
- [Maintaining Common Ground in Dynamic Environments](https://mlsanity.com/paper/2105.14207/) (2021)
- [Resolving References in Visually-Grounded Dialogue via Text Generation](https://mlsanity.com/paper/2309.13430/) (2023)
- [Can Visual Dialogue Models Do Scorekeeping? Exploring How Dialogue Representations Incrementally Encode Shared Knowledge](https://mlsanity.com/paper/2204.06970/) (2022)
- [Modeling Non-Cooperative Dialogue: Theoretical and Empirical Insights](https://mlsanity.com/paper/2207.07255/) (2022)
- [Using Game Play to Investigate Multimodal and Conversational Grounding in Large Multimodal Models](https://mlsanity.com/paper/2406.14035/) (2024)
- [Collecting Visually-Grounded Dialogue with A Game Of Sorts](https://mlsanity.com/paper/2309.05162/) (2023)
- [Collaborative Problem-Solving in an Optimization Game](https://mlsanity.com/paper/2505.15490/) (2025)
- [We went to look for meaning and all we got were these lousy representations: aspects of meaning representation for computational semantics](https://mlsanity.com/paper/2109.04949/) (2021)

## Abstract (arXiv)

Where early work on dialogue in Computational Linguistics put much emphasis on dialogue structure and its relation to the mental states of the dialogue participants (e.g., Allen 1979, Grosz & Sidner 1986), current work mostly reduces dialogue to the task of producing at any one time a next utterance; e.g. in neural chatbot or Visual Dialogue settings. As a methodological decision, this is sound: Even the longest journey is a sequence of steps. It becomes detrimental, however, when the tasks and datasets from which dialogue behaviour is to be learned are tailored too much to this framing of the problem. In this short note, we describe a family of settings which still allow to keep dialogues simple, but add a constraint that makes participants care about reaching mutual understanding. In such agreement games, there is a secondary, but explicit goal besides the task level goal, and that is to reach mutual understanding about whether the task level goal has been reached. As we argue, this naturally triggers meta-semantic interaction and mutual engagement, and hence leads to richer data from which to induce models.