Papers with CGT
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
| Challenge: | In dialogue modeling, there is considerable attention on “dialogue state tracking” (DST) but “common ground tracking” identifies the shared belief space held by all participants in a task-oriented dialogue: the task-relevant propositions all participants accept as true. |
| Approach: | They propose a method for automatically identifying the current set of shared beliefs and ”questions under discussion” of a group with a shared goal. |
| Outcome: | The proposed method predicts moves toward building common ground relative to ground truth in a multimodal interaction with an AI. |
Controlled Transformation of Text-Attributed Graphs (2024.findings-emnlp)
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| Challenge: | Graph generation is the process of generating new graphs with similar attributes to real world graphs. |
| Approach: | They propose a controllable multi-objective translation model for text-attributed graphs that can translate a given source graph to a target graph while satisfying multiple desired graph attributes at granular level. |
| Outcome: | The proposed model can translate a given source graph to a target graph while satisfying multiple desired graph attributes at granular level. |