Geometry of Compositionality
Not on the map. Why?
Abstract (arXiv)
This paper proposes a simple test for compositionality (i.e., literal usage) of a word or phrase in a context-specific way. The test is computationally simple, relying on no external resources and only uses a set of trained word vectors. Experiments show that the proposed method is competitive with state of the art and displays high accuracy in context-specific compositionality detection of a variety of natural language phenomena (idiomaticity, sarcasm, metaphor) for different datasets in multiple languages. The key insight is to connect compositionality to a curious geometric property of word embeddings, which is of independent interest.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Nov 2016.
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Citing papers per year: 2021: 3; 2022: 0; 2023: 0; 2024: 0; 2025: 1.
4 papers.
- 2021Idiomatic Expression Identification using Semantic Compatibilitycited by 19
- 2021Idiomatic Expression Paraphrasing without Strong Supervisioncited by 7
- 2021From Solving a Problem Boldly to Cutting the Gordian Knot: Idiomatic Text Generationcited by 5
- 2025Understanding Subword Compositionality of Large Language Modelscited by 3
- 2025Understanding Subword Compositionality of Large Language Models25 Aug 2025
- 2021Idiomatic Expression Paraphrasing without Strong Supervision16 Dec 2021
- 2021Idiomatic Expression Identification using Semantic Compatibility19 Oct 2021
- 2021From Solving a Problem Boldly to Cutting the Gordian Knot: Idiomatic Text Generation13 Apr 2021