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Found 5 papers, 1 papers with code
Asymmetric Mutual Learning for Multi-source Unsupervised Sentiment Adaptation with Dynamic Feature Network
Recently, fine-tuning the pre-trained language model (PrLM) on labeled sentiment datasets demonstrates impressive performance.
Learning Robust Self-attention Features for Speech Emotion Recognition with Label-adaptive Mixup
Speech Emotion Recognition (SER) is to recognize human emotions in a natural verbal interaction scenario with machines, which is considered as a challenging problem due to the ambiguous human emotions.
Window transformer for dialogue document: a joint framework for causal emotion entailment
The Causal Emotion Entailment (CEE) task aims to extract all potential pairs of emotions and corresponding causes from the unannotated emotion document in the conversational context.
Ranked #2 on
Causal Emotion Entailment
on RECCON
CSAT‑FTCN: A Fuzzy‑Oriented Model with Contextual Self‑attention Network for Multimodal Emotion Recognition
Moreover, the CSAT-FTCN can obtain the dependency relationships of target utterances on internal own key information and external contextual information to understand emotions in a more profound sense.
Reconstructing 3D Model from Single-View Sketch with Deep Neural Network
It creates the transformation representation of a sketch by extracting the shape features of an input sketch and transformation template samples.
