כתבה
arXiv cs.AI ·
StanceFlip: בסיס מלא לבדיקה רב-ממדית לפניה לעמדה חדשה בשיחות רב-מודליות
StanceFlip: A Comprehensive Multi-Dimensional Benchmark for Multimodal Conversational Stance Flipping Forecasting
בסיס חדש לבדיקה של פניה לעמדה חדשה בשיחות רב-מודליות, כולל מודלי GPT-5.
תקציר מקורי באנגליתarXiv:2607.24191v1 Announce Type: cross Abstract: Conversational stance detection has shifted from static text analysis to dynamic multimodal modeling. However, existing benchmarks exhibit three key limitations: failure to capture the dynamic evolution of beliefs, particularly during stance reversals; difficulty in disentangling affective states from logical reasoning; and neglect of the critical role of multimodal cues in resolving pragmatic ambiguities such as sarcasm. To address these limitations, we propose StanceFlip, a benchmark designed for multimodal conversational stance flipping forecasting over multi-turn dialogues across five modalities and multi-scenarios, which includes two novel subtasks: 1) Multimodal Stance Sextuple Extraction, extracting holder, target, emotion, sentiment
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arxiv.org
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