# BOS at LSCDiscovery: Lexical Substitution for Interpretable Lexical Semantic Change Detection

arXiv: https://arxiv.org/abs/2206.11865 · HTML: https://mlsanity.com/paper/2206.11865/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 14 references that are in the map.
- First posted on arXiv 7 Jun 2022.

## Builds on (most cited first, 7 of 7)

- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [Analysing Lexical Semantic Change with Contextualised Word Representations](https://mlsanity.com/paper/2004.14118/) (2020)
- [Explaining and Improving BERT Performance on Lexical Semantic Change Detection](https://mlsanity.com/paper/2103.07259/) (2021)
- [Word Sense Induction with Neural biLM and Symmetric Patterns](https://mlsanity.com/paper/1808.08518/) (2018)
- [Towards better substitution-based word sense induction](https://mlsanity.com/paper/1905.12598/) (2019)
- [LSCDiscovery: A shared task on semantic change discovery and detection in Spanish](https://mlsanity.com/paper/2205.06691/) (2022)
- [Combining Neural Language Models for WordSense Induction](https://mlsanity.com/paper/2006.13200/) (2020)

## Built on by (most cited first, 2 of 2)

- [A Survey on Contextualised Semantic Shift Detection](https://mlsanity.com/paper/2304.01666/) (2023)
- [Substitution-based Semantic Change Detection using Contextual Embeddings](https://mlsanity.com/paper/2309.02403/) (2023)

## Abstract (arXiv)

We propose a solution for the LSCDiscovery shared task on Lexical Semantic Change Detection in Spanish. Our approach is based on generating lexical substitutes that describe old and new senses of a given word. This approach achieves the second best result in sense loss and sense gain detection subtasks. By observing those substitutes that are specific for only one time period, one can understand which senses were obtained or lost. This allows providing more detailed information about semantic change to the user and makes our method interpretable.