Beyond frequency measures: Can contextual embeddings capture meaning change in scientific texts?

Paper recorded by Signals 4 on 2026-09-16 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-16 on arXiv · recorded by Signals 4 on 2026-09-17

Category: cs.CL · 自然语言处理 · first seen 2026-09-17

Abstract

Identifying technological trends is a core scientometric task, yet traditional frequency-based approaches struggle to capture substantial meaning shifts of domain-specific terms. We hypothesise that contextual embeddings can complement frequency dynamics to effectively track diachronic semantic change. We compare frequency and embedding-based approaches across Astrophysics and NLP corpora spanning

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