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Found 19 papers, 5 papers with code
A Systematic Comparison of Contextualized Word Embeddings for Lexical Semantic Change
Our evaluation is performed across different languages on eight available benchmarks for LSC, and shows that (i) APD outperforms other approaches for GCD; (ii) XL-LEXEME outperforms other contextualized models for WiC, WSI, and GCD, while being comparable to GPT-4; (iii) there is a clear need for improving the modeling of word meanings, as well as focus on how, when, and why these meanings change, rather than solely focusing on the extent of semantic change.
(Chat)GPT v BERT: Dawn of Justice for Semantic Change Detection
In the universe of Natural Language Processing, Transformer-based language models like BERT and (Chat)GPT have emerged as lexical superheroes with great power to solve open research problems.
The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Change
We present the DURel tool that implements the annotation of semantic proximity between uses of words into an online, open source interface.
Computational modeling of semantic change
In this chapter we provide an overview of computational modeling for semantic change using large and semi-large textual corpora.
DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages
Word meaning is notoriously difficult to capture, both synchronically and diachronically.
SuperSim: a test set for word similarity and relatedness in Swedish
Language models are notoriously difficult to evaluate.
Challenges for Computational Lexical Semantic Change
The computational study of lexical semantic change (LSC) has taken off in the past few years and we are seeing increasing interest in the field, from both computational sciences and linguistics.
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection
Lexical Semantic Change detection, i. e., the task of identifying words that change meaning over time, is a very active research area, with applications in NLP, lexicography, and linguistics.
Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change
State-of-the-art models of lexical semantic change detection suffer from noise stemming from vector space alignment.
Survey of Computational Approaches to Lexical Semantic Change
In this article we focus on diachronic conceptual change as an extension of semantic change.
Finding Individual Word Sense Changes and their Delay in Appearance
We present a method for detecting word sense changes by utilizing automatically induced word senses.
Parameter Transfer across Domains for Word Sense Disambiguation
Word sense disambiguation is defined as finding the corresponding sense for a target word in a given context, which comprises a major step in text applications.
Named Entity Evolution Recognition on the Blogosphere
We approach these by adapting an existing NEER method to work on noisy data like the Web and the Blogosphere in particular.
