e-ISSN: Pending
Negative / Null Result ReportOpen accessComputer Science

Persuasive Dialogue Understanding: the Baselines and Negative Results

Hui Chen; Deepanway Ghosal; Navonil Majumder; Amir Hussain; Soujanya Poria · 2020 · arXiv

WASTE classifies this as Negative / Null Result Report · AI classification, approximate

The study found no significant effect — useful as a negative control or null benchmark for your own design.

Abstract (excerpt)

Persuasion aims at forming one's opinion and action via a series of persuasive messages containing persuader's strategies. Due to its potential application in persuasive dialogue systems, the task of persuasive strategy recognition has gained much attention lately. Previous methods on user intent recognition in dialogue systems adopt recurrent neural network (RNN) or convolutional neural network (CNN) to model context in conversational history, neglecting the tactic history and intra-speaker relation. In this paper, we demonstrate the limitations of a Transformer-based approach coupled with Co

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Metadata source: arXiv