Papers with context-specific representations

2 papers
How Contextual are Contextualized Word Representations? Comparing the Geometry of BERT, ELMo, and GPT-2 Embeddings (D19-1)

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Challenge: Existing word embeddings were static, requiring all senses of a polysemous word to share the same representation.
Approach: They found that the contextualized representations of all words are not isotropic in any layer of the contextualizing model.
Outcome: The results show that the representations of all words are not isotropic in any layer of the contextualizing model.
Self-adaptive Context and Modal-interaction Modeling For Multimodal Emotion Recognition (2023.findings-acl)

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Challenge: Existing methods to predict emotion label for a given utterance lack modeling of diverse dependency ranges and inconsistent treatment of contribution for various modalities.
Approach: They propose a multimodal emotion recognition in conversation task that uses context and multiple modalities to predict emotion label for a given utterance.
Outcome: The proposed method outperforms the state-of-the-art methods on three multimodal datasets.

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