Seneviratne, SandaruDaskalaki, ElenaLenskiy, ArtemSuominen, Hanna2026-03-242026-03-242951-2093ORCID:/0000-0002-4195-1641/work/209320650https://hdl.handle.net/1885/733807740Lexical substitution, which aims to generate substitutes for a target word given a context, is an important natural language processing task useful in many applications. Due to the paucity of annotated data, existing methods for lexical substitution tend to rely on manually curated lexical resources and contextual word embedding models. Methods based on lexical resources are likely to miss relevant substitutes whereas relying only on contextual word embedding models fails to provide adequate information on the impact of a substitute in the entire context and the overall meaning of the input. We proposed CILex, which uses contextual sentence embeddings along with methods that capture additional Context Information complimenting contextual word embeddings for Lexical substitution. This ensured the semantic consistency of a substitute with the target word while maintaining the overall meaning of the sentence. Our experimental comparisons with previously proposed methods indicated that our solution is now the state-of-the-art on both the widely used LS07 and CoInCo datasets with P@1 scores of 55.96% and 57.25% for lexical substitution. The implementation of the proposed approach is available at https://github.com/sandaruSen/CILex under the MIT license.This research was funded by and has been delivered in partnership with Our Health in Our Hands (OHIOH), a strategic initiative of the ANU, which aims to transform health care by developing new personalised health technologies and solutions in collaboration with patients, clinicians and healthcare providers. We gratefully acknowledge the funding from the ANU School of Computing for the first author’s PhD studies. We wish to thank the reviewers for their valuable comments. We also thank the authors of Arefyev et al. (2020a); Michalopoulos et al. (2022) for releasing their code and clarifying the questions we came across.12enPublisher Copyright: © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.202285162092728