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cs.CL2024
AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation
Xiyuan Gao, Shubhi Bansal, Kushaan Gowda +4
Detecting sarcasm effectively requires a nuanced understanding of context, including vocal tones and facial expressions. The progression towards multimodal computational methods in…
cs.CL2024
A Functional Trade-off between Prosodic and Semantic Cues in Conveying Sarcasm
Zhu Li, Xiyuan Gao, Yuqing Zhang +2
This study investigates the acoustic features of sarcasm and disentangles the interplay between the propensity of an utterance being used sarcastically and the presence of prosodic…
cs.CV2024
Disentangled Pre-training for Human-Object Interaction Detection
Zhuolong Li, Xingao Li, Changxing Ding +1
Detecting human-object interaction (HOI) has long been limited by the amount of supervised data available. Recent approaches address this issue by pre-training according to pseudo-…