Reflect, Not Reflex: Inference-Based Common Ground Improves Dialogue Response Quality (2022.emnlp-main)
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| Challenge: | Currently, human communication models fail to explicitly model common ground (CG) . less than half of the responses in current data is rated as high quality . |
| Approach: | They propose a dataset that annotates dialogues with explicit CG and solicits 9k diverse responses each following one common ground. |
| Outcome: | The proposed dataset annotates dialogues with explicit CG and solicits 9k diverse responses each following one common ground. |
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| Challenge: | Currently, response generation (RG) models do not understand human communication intents. |
| Approach: | They propose to examine commonsense reasoning implicitly to determine whether RG models produce coherent responses in conversations. |
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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 . |
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Finding Common Ground: Annotating and Predicting Common Ground in Spoken Conversations (2023.findings-emnlp)
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| Challenge: | Creating and updating common ground (CG) between interlocutors is the key to a successful conversation. |
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| Challenge: | Existing approaches to train grounded dialogues require large amounts of data. |
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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. |
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| Challenge: | Xu et al., 2023) and Bai ed., 2019) use crowdworkers to collect signals from natural dialogue episodes. |
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Pan More Gold from the Sand: Refining Open-domain Dialogue Training with Noisy Self-Retrieval Generation (2022.coling-1)
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| Challenge: | Existing methods for generating open-domain dialogue systems underutilize training data. |
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Common Ground Tracking in Multimodal Dialogue (2024.lrec-main)
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Ibrahim Khalil Khebour, Kenneth Lai, Mariah Bradford, Yifan Zhu, Richard A. Brutti, Christopher Tam, Jingxuan Tu, Benjamin A. Ibarra, Nathaniel Blanchard, Nikhil Krishnaswamy, James Pustejovsky
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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. |
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Grounding in social media: An approach to building a chit-chat dialogue model (2022.naacl-srw)
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| Challenge: | Existing open-domain dialogue models fail to capture and utilize external knowledge, leading to repetitive or generic responses to unseen utterances. |
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