Papers with Generating metaphors

2 papers
MERMAID: Metaphor Generation with Symbolism and Discriminative Decoding (2021.naacl-main)

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Challenge: a new method for generating metaphors is proposed to generate literal sentences . human evaluations show that our best model generates metaphors better than three well-crafted baselines 66% of the time on average.
Approach: They propose a method to automatically construct a parallel corpus by transforming literal sentences to metaphorical ones using commonsense inference and masked language modeling.
Outcome: The proposed method generates metaphors better than baselines 66% of the time on average.
Metaphor Generation with Conceptual Mappings (2021.acl-long)

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Challenge: Existing models for metaphor generation lack conceptualization of meaning of the metaphors . recent neural models have led to advances in many areas of natural language generation .
Approach: They propose to encode conceptual mappings between cognitive domains to generate metaphoric expressions by embedding verbs into a literal expression and deriving source/target pairs to train a controlled seq-to-seq generation model.
Outcome: The proposed method outperforms existing models in automatic and human evaluations for basic metaphoricity and conceptual metaphor presence.

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