Dialogue Summarization with Emotion Dynamics Using Topic- and Participant-Centric Decomposition
Existing text summarization research has focused much on monologic information (e.g., newspaper articles, reports) without accounting for the interaction between speakers or authors. In contrast, dialogues are a rich communication channel where multiple participants conduct back and forth exchanges to construct meaning. We propose a dialogue summarization framework that explicitly models both semantic and emotion dynamics using multimodal dialogue inputs, built on an adapted hierarchical Chain-of-Agents approach. We decompose dialogues from two perspectives: (1) topic segments based on the utt
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- LinkedLinked via arxiv author · 85%Linyun Xiang →
“Dialogue Summarization with Emotion Dynamics Using Topic- and Participant-Centric Decomposition”
- LinkedLinked via arxiv author · 85%Mark Neerincx →
“Dialogue Summarization with Emotion Dynamics Using Topic- and Participant-Centric Decomposition”
- LinkedLinked via arxiv author · 85%Stephanie Tan →
“Dialogue Summarization with Emotion Dynamics Using Topic- and Participant-Centric Decomposition”
- FuzzySimilar title/name (fuzzy) · 87%MaartenGr/BERTopic →
“Fuzzy title match (0.94): “Dialogue Summarization with Emotion Dynamics Using Topic- an” ≈ “MaartenGr/BERTopic””