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Neural Metaphor Detection in Context

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arxiv 1808.09653 v1 pith:QNGC6WGW submitted 2018-08-29 cs.CL

Neural Metaphor Detection in Context

classification cs.CL
keywords contextmodelsdetectionmetaphorneuralworkbenchmarksbilstm
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We present end-to-end neural models for detecting metaphorical word use in context. We show that relatively standard BiLSTM models which operate on complete sentences work well in this setting, in comparison to previous work that used more restricted forms of linguistic context. These models establish a new state-of-the-art on existing verb metaphor detection benchmarks, and show strong performance on jointly predicting the metaphoricity of all words in a running text.

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  1. When Meaning Travels: A Granular Lens on Hybrid-MoE's Role in Idiomatic Understanding for Language Models

    cs.CL 2026-06 unverdicted novelty 5.0

    HybridMoE with controlled hybridization and idiomatic property signals yields 5-6% gains in figurative language representation for multilingual vision-language models.