Pierluigi Cassotti, Naomi Baes, Stefano De Pascale, Jáder Martins Camboim de Sá, Francesco Periti, Nick Haslam, Dirk Geeraerts, Nina Tahmasebi. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

There is abundant evidence of the fact that the way words change their meaning can be classified in different types of change, highlighting the relationship between the old and new meanings (among which generalization, specialization and co-hyponymy transfer).In this paper, we present a way of detecting these types of change by constructing a model that leverages information both from synchronic lexical relations and definitions of word meanings.Specifically, we use synset definitions and hierarchy information from WordNet and test it on a digitized version of Blank's (1997) dataset of semantic change types.Finally, we show how the sense relationships can improve models for both approximation of human judgments of semantic relatedness as well as binary Lexical Semantic Change Detection.

Numerical design and planning problems can often be formulated conveniently as a set of equations constraining the values of related variables, i.e., as a numerical or more generally as an interval constraint satisfaction problem (ICSP). However, due to theoretical and practical problems, no tools for solving ICSPs properly in the general case have thus far been designed and implemented. The authors discuss both theoretical and practical problems of solving ICSPs, and present solution approaches taken in the new interval constraint satisfaction tool INC++. The tool can be applied, for example, as the basis for next generation interval constraint spreadsheets.