Papers with Multimodal Transformer

2 papers
Multiˆ2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERT (2020.findings-emnlp)

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Challenge: Existing open IE systems were based on handcrafted features or fine-grained rules.
Approach: They propose a multi-head argument extraction method using multi-lingual BERT . they use a query, key, and value setting inspired by the Multimodal Transformer .
Outcome: The proposed method outperforms existing sequence-labeling systems on two benchmark datasets and on two languages without training data.
Multimodal Transformer for Unaligned Multimodal Language Sequences (P19-1)

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Challenge: Human language is often multimodal, which comprehends a mixture of natural language, facial gestures, and acoustic behaviors.
Approach: They propose a multimodal model that extends the standard Transformer network to learn representations directly from unaligned multimodal streams.
Outcome: The proposed model outperforms state-of-the-art methods on aligned and non-aligned data.

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