| Challenge: | a new study shows that dialog requires a collaborative grounding approach to ground meaning . the problem is that dialog partners are not able to ground themselves . |
| Approach: | They argue that it is missing from current deep learning approaches to dialog . they argue that making mistakes and being able to recover from them is key . |
| Outcome: | The proposed model is based on the language acquisition and dialog systems literature . it shows that making mistakes and being able to recover from them is key . |
Similar Papers
Achieving Common Ground in Multi-modal Dialogue (2020.acl-tutorials)
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| Challenge: | tutorial focuses on three main topic areas: grounding in human-human communication, dialogue systems and multi-modal interactive systems. |
| Approach: | This tutorial examines the use of computational dialogue research to design grounding modules and behaviors in cutting-edge systems. |
| Outcome: | This tutorial examines the results of recent research on grounding in human-human communication . it shows how these results lead to rich and challenging opportunities for doing grounding more flexible and powerful ways . |
Grounding ‘Grounding’ in NLP (2021.findings-acl)
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| Challenge: | Cognitive Science defines "grounding" as the process of establishing mutual information between two interlocutors. |
| Approach: | They examine the gaps between NLP and Cognitive Science definitions of "grounding" they propose ways to create new tasks or repurpose existing ones to achieve a more complete sense of grounding . |
| Outcome: | The authors examine the gaps between definitions of grounding and cognitive science . they show that there are ways to improve existing tasks or repurpose existing ones . |
A Speculative and Tentative Common Ground Handling for Efficient Composition of Uncertain Dialogue (2022.lrec-1)
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| Challenge: | a study explores how the grounding process is composed and adapts to human cognitive processes . common ground is a set of information shared among participants that serves as a precondition for understanding individual utterances . |
| Approach: | a study investigates how the grounding process is composed by participants . it suggests that common ground may not necessarily be formed bottom-up through analytic expressions . |
| Outcome: | a new approach to human-like dialogue may be more suitable for natural human communication, the authors say . they show that common ground is mutually accepted among participants through holistic expressions . |
Conversational Grounding: Annotation and Analysis of Grounding Acts and Grounding Units (2024.lrec-main)
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| Challenge: | Successful conversations often rest on common understanding, says a researcher . despite recent advances in dialog systems, there is a noticeable deficit in their grounding capabilities . |
| Approach: | They propose to use a framework to build conversational grounding in dialogs . they propose to analyze two dialog corpora using grounding acts and grounding units . |
| Outcome: | The proposed model shows that language models are not enough to ground dialogs with machines . the proposed model can be used to test the performance of existing Language Models . |
Grounding Conversations with Improvised Dialogues (2020.acl-main)
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| Challenge: | Effective dialogue involves grounding, the process of establishing mutual knowledge that is essential for communication between people. |
| Approach: | a new study uses a corpus of yes-and-turns to analyze improv dialogues . they find that dialogue is a collaborative process by which partners coordinate via turns or acts to jointly construct a common world state. |
| Outcome: | a new study fine-tunes chit-chat dialogue systems with their corpus to encourage more grounded, relevant conversation. |
Learning Language through Grounding (2025.naacl-tutorial)
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| Challenge: | This tutorial provides a historical overview of grounding and discusses its use in computational linguistics and in computational language processing. |
| Approach: | They introduce the concept of grounding and discuss future directions and open challenges . they will delve into recent progress in learning lexical semantics, syntax, and complex meanings through various forms of ground. |
| Outcome: | This course will provide an overview of the field of grounding and discuss future directions and challenges related to large language models and scaling. |
Frame of Reference: Addressing the Challenges of Common Ground Representation in Situational Dialogs (2026.findings-acl)
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| Challenge: | Prior studies have demonstrated that Large Language Models (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. |
| Approach: | They propose to use relational references to represent common ground in situated dialogues and propose to improve both the establishment of common ground and its subsequent use in the conversation. |
| Outcome: | The proposed models can establish and exploit common ground in situated dialogues and improve its subsequent use. |
Grounding Gaps in Language Model Generations (2024.naacl-long)
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| Challenge: | Effective conversation requires common ground, but it does not emerge spontaneously. |
| Approach: | They propose a set of grounding acts and metrics that quantify attempted grounding . they find that large language models generate language with less conversational grounding than humans . |
| Outcome: | The proposed models generate language with less conversational grounding than humans . compared to humans, they generate language that appears to presume common ground . |
Maintaining Common Ground in Dynamic Environments (2021.tacl-1)
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| Challenge: | Existing task settings focus on creating and maintaining common ground under static contexts and ignore their dynamic aspects. |
| Approach: | They propose a task setting to study the ability of creating and maintaining common ground in dynamic environments. |
| Outcome: | The proposed task setting enables fine-grained evaluation and analysis of various dialogue systems. |
Understanding Common Ground Misalignment in Goal-Oriented Dialog: A Case-Study with Ubuntu Chat Logs (2025.acl-long)
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| Challenge: | a misalignment or misunderstanding can disrupt communication, leading to confusion or conflict. |
| Approach: | They study failures of grounding in Ubuntu IRC datasets to identify misalignments . they find disruptions in conversational flow are driven by a divergence in beliefs . |
| Outcome: | The findings show that misalignment in common ground can disrupt communication . the study also shows that miscommunications can lead to confusion or conflict . |