# Conversational Grounding: Annotation and Analysis of Grounding Acts and Grounding Units

arXiv: https://arxiv.org/abs/2403.16609 · HTML: https://mlsanity.com/paper/2403.16609/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 50 references that are in the map.
- First posted on arXiv 25 Mar 2024.

## Builds on (most cited first, 17 of 17)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [TEACh: Task-driven Embodied Agents that Chat](https://mlsanity.com/paper/2110.00534/) (2021)
- [MindCraft: Theory of Mind Modeling for Situated Dialogue in Collaborative Tasks](https://mlsanity.com/paper/2109.06275/) (2021)
- [GODEL: Large-Scale Pre-Training for Goal-Directed Dialog](https://mlsanity.com/paper/2206.11309/) (2022)
- [The PhotoBook Dataset: Building Common Ground through Visually-Grounded Dialogue](https://mlsanity.com/paper/1906.01530/) (2019)
- [Talk the Walk: Navigating New York City through Grounded Dialogue](https://mlsanity.com/paper/1807.03367/) (2018)
- [A Natural Language Corpus of Common Grounding under Continuous and Partially-Observable Context](https://mlsanity.com/paper/1907.03399/) (2019)
- [MeetUp! A Corpus of Joint Activity Dialogues in a Visual Environment](https://mlsanity.com/paper/1907.05084/) (2019)
- [Reference-Centric Models for Grounded Collaborative Dialogue](https://mlsanity.com/paper/2109.05042/) (2021)
- [Conversation as Action Under Uncertainty](https://mlsanity.com/paper/1301.3883/) (2013)
- [Maintaining Common Ground in Dynamic Environments](https://mlsanity.com/paper/2105.14207/) (2021)
- [The Spot the Difference corpus: a multi-modal corpus of spontaneous task oriented spoken interactions](https://mlsanity.com/paper/1805.05091/) (2018)
- [The Open-domain Paradox for Chatbots: Common Ground as the Basis for Human-like Dialogue](https://mlsanity.com/paper/2303.11708/) (2023)

## Built on by (most cited first, 9 of 9)

- [Understanding Common Ground Misalignment in Goal-Oriented Dialog: A Case-Study with Ubuntu Chat Logs](https://mlsanity.com/paper/2503.12370/) (2025)
- [Characterizing Language Use in a Collaborative Situated Game](https://mlsanity.com/paper/2512.03381/) (2025)
- [PoliCon: Evaluating LLMs on Achieving Diverse Political Consensus Objectives](https://mlsanity.com/paper/2505.19558/) (2025)
- [Frame of Reference: Addressing the Challenges of Common Ground Representation in Situational Dialogs](https://mlsanity.com/paper/2601.09365/) (2026)
- [It Couldn't Help But Overhear: On the Limits of Modelling Meta-Communicative Grounding Acts with Supervised Learning](https://mlsanity.com/paper/2405.01139/) (2024)
- [Bridging Information Gaps in Dialogues With Grounded Exchanges Using Knowledge Graphs](https://mlsanity.com/paper/2408.01088/) (2024)
- [Using Machine Mental Imagery for Representing Common Ground in Situated Dialogue](https://mlsanity.com/paper/2604.21144/) (2026)
- [Illusion of Alignment: Detecting Hidden Disagreement in Collaborative Dialogue](https://mlsanity.com/paper/2608.08210/) (2026)
- [Knowing the User Is Not Knowing What We Established: Grounding Awareness in Personal Agents](https://mlsanity.com/paper/2610.18684/) (2026)

## Abstract (arXiv)

Successful conversations often rest on common understanding, where all parties are on the same page about the information being shared. This process, known as conversational grounding, is crucial for building trustworthy dialog systems that can accurately keep track of and recall the shared information. The proficiencies of an agent in grounding the conveyed information significantly contribute to building a reliable dialog system. Despite recent advancements in dialog systems, there exists a noticeable deficit in their grounding capabilities. Traum provided a framework for conversational grounding introducing Grounding Acts and Grounding Units, but substantial progress, especially in the realm of Large Language Models, remains lacking. To bridge this gap, we present the annotation of two dialog corpora employing Grounding Acts, Grounding Units, and a measure of their degree of grounding. We discuss our key findings during the annotation and also provide a baseline model to test the performance of current Language Models in categorizing the grounding acts of the dialogs. Our work aims to provide a useful resource for further research in making conversations with machines better understood and more reliable in natural day-to-day collaborative dialogs.