The content discusses the application of social orientation tags in predicting and explaining dialogue outcomes. It highlights the importance of understanding social orientations in conversations and how they impact success or failure. The study showcases the utility of these tags in improving accuracy and explainability in dialogue outcome prediction tasks.
The authors introduce a new data set labeled with social orientation tags, showing how these features enhance neural models' performance on English and Chinese dialogue benchmarks. They demonstrate that incorporating social orientation features improves model accuracy, especially in low-resource settings. The study emphasizes the significance of using social orientation tags for better dialogue outcome predictions.
Furthermore, the content delves into related work, data collection methods, model training, experiments, results showcasing state-of-the-art performance, explainability through circumplex theory, qualitative analysis of conversation samples with social orientation tags, and future research directions.
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arxiv.org
ข้อมูลเชิงลึกที่สำคัญจาก
by Todd Morrill... ที่ arxiv.org 03-11-2024
https://arxiv.org/pdf/2403.04770.pdfสอบถามเพิ่มเติม