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The Effect of Round-Trip Translation on Fairness in Sentiment Analysis ...
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MATE: Multi-view Attention for Table Transformer Efficiency ...
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Argument Pair Extraction with Mutual Guidance and Inter-sentence Relation Graph ...
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Joint Multi-modal Aspect-Sentiment Analysis with Auxiliary Cross-modal Relation Detection ...
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Comparative Opinion Quintuple Extraction from Product Reviews ...
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PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction ...
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Natural language processing as a tool to identify the Reddit particularities of cancer survivors around the time of diagnosis and remission: A pilot study ...
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A Large-Scale Dataset for Empathetic Response Generation ...
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YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviews ...
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Sample Selection Guided by Domain and Task for Cross-Domain Targeted Sentiment Analysis ...
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Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training ...
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Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis ...
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Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment Analysis with Affective Knowledge ...
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Unimodal and Crossmodal Refinement Network for Multimodal Sequence Fusion ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.720/ Abstract: Effective unimodal representation and complementary crossmodal representation fusion are both important in multimodal representation learning. Prior works often modulate one modal feature to another straightforwardly and thus, underutilizing both unimodal and crossmodal representation refinements, which incurs a bottleneck of performance improvement. In this paper, Unimodal and Crossmodal Refinement Network (UCRN) is proposed to enhance both unimodal and crossmodal representations. Specifically, to improve unimodal representations, a unimodal refinement module is designed to refine modality-specific learning via iteratively updating the distribution with transformer-based attention layers. Self-quality improvement layers are followed to generate the desired weighted representations progressively. Subsequently, those unimodal representations are projected into a common latent space, regularized by a multimodal Jensen-Shannon ...
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Keyword:
Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Sentiment Analysis
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URL: https://underline.io/lecture/37323-unimodal-and-crossmodal-refinement-network-for-multimodal-sequence-fusion https://dx.doi.org/10.48448/6m8y-q898
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Reinforced Counterfactual Data Augmentation for Dual Sentiment Classification ...
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Seeking Common but Distinguishing Difference, A Joint Aspect-based Sentiment Analysis Model ...
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