On the Compositionality Prediction of Noun Phrases using Poincaré Embeddings (P19-1)
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| Challenge: | idiomatic phrases have a non-compositional meaning, meanings of which can be derived from constituents and their grammatical relations. |
| Approach: | They propose to combine hierarchical and distributional information to blend hierarchic and distribution-based hierarchies to detect compositionality for noun phrases. |
| Outcome: | The proposed technique achieves significant improvements over state-of-the-art models based on distributional information and a weighted average of the distributional similarity and p-like function. |
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Quantifying Compositionality of Classic and State-of-the-Art Embeddings (2025.findings-emnlp)
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| Challenge: | Static word embeddings make strong claims about compositionality, but the SOTA generative models go too far in the other direction. |
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A Large Automatically-Acquired All-Words List of Multiword Expressions Scored for Compositionality (L18-1)
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| Challenge: | Existing literature on semantically idiosyncratic multiword expressions is limited to English . idiomatic expressions are phraseological units consisting of more than one lexeme and exhibit some kind of idiom. |
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Additive Compositionality of Word Vectors (D19-55)
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| Challenge: | contextual language models are dominant in the field of Natural Language Processing, but they are not suitable for all uses. |
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An Unsupervised Method for Learning Representations of Multi-word Expressions for Semantic Classification (2020.coling-main)
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| Challenge: | Existing methods for learning multi-word expressions have language sparsity and are not supervised. |
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Modeling the Evolution of English Noun Compounds with Feature-Rich Diachronic Compositionality Prediction (2025.acl-long)
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| Challenge: | Empirical research directly addressing these issues is limited to a small number of studies suggesting that compounding is a highly productive process. |
| Approach: | They represent English noun compounds as vectors of time-specific values and implement a set of features to classify them for present-day compositionality and assess the informativeness of the corresponding linguistic patterns. |
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Are representations built from the ground up? An empirical examination of local composition in language models (2022.emnlp-main)
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| Challenge: | Compositionality is a hallmark of human language, but many phrases are non-compositional . a study by a team of researchers shows that LMs may not be able to distinguish between compositional and non-composable phrases. |
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Variants of Vector Space Reductions for Predicting the Compositionality of English Noun Compounds (2020.lrec-1)
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| Challenge: | Existing approaches to predict the degree of compositionality of noun compounds are based on comparing compounds and their constituents within a vector space and using distributional similarity as a proxy to predict their degree of semantic relatedness. |
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Non-Compositionality in Sentiment: New Data and Analyses (2023.findings-emnlp)
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| Challenge: | Many studies on sentiment analysis focus on the fact that sentiment computations are compositional . linguistic utterances often do not adhere to strict patterns and can be surprising when looking at the individual words involved. |
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