| Challenge: | Using Visibility Embeddings, sequence metaphor labeling is improved . many metaphors involve noticeable differences between the abstractness of words constructing them . |
| Approach: | They propose to concatenate sequence metaphor labeling with BiLSTM inputs to obtain improvements . they use visibility embeddings to provide a good estimation of a word's concreteness . |
| Outcome: | The proposed method improves the problem of sequence metaphor labeling with BERT . it allows for consistent and significant improvements at almost no cost . |
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| Challenge: | a lack of comparable multilingual benchmarks and a consensual evaluation protocol for contextual models remains an open question. |
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VOLIMET: A Parallel Corpus of Literal and Metaphorical Verb-Object Pairs for English–German and English–French (2024.starsem-1)
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Representation of Lexical Stylistic Features in Language Models’ Embedding Space (2023.starsem-1)
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DRS Parsing as Sequence Labeling (2022.starsem-1)
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Guiding Zero-Shot Paraphrase Generation with Fine-Grained Control Tokens (2023.starsem-1)
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Overcoming Poor Word Embeddings with Word Definitions (2021.starsem-1)
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