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

arXiv:2609.18804 · cs.CL · Submitted 2026-09-16 · Read on arXiv

cs.CL

Submitted: 2026-09-16

Updated: 2026-09-16

Journal ref: 18th International Conference on Statistical Analysis of Textual Data (JADT 2026), Jul 2026, Palermo, Italy. pp.232-241

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Embeddings — 30× in this paper · explained in 2 episodes
Maximum Mean Discrepancy — 6× in this paper
Average Pairwise Distance — 4× in this paper
Core — 3× in this paper · explained in 2 episodes
Semantic Drift — 3× in this paper · explained in 3 episodes
Ablation — 2× in this paper · explained in 1 episode
Alignment — 2× in this paper · explained in 1 episode
Consistency — 2× in this paper · explained in 3 episodes
Decoupling — 2× in this paper · explained in 2 episodes
Vector Representations — 2× in this paper · explained in 2 episodes
Adaptation — 1× in this paper · explained in 1 episode
Benchmark — 1× in this paper · explained in 2 episodes
Calibration — 1× in this paper · explained in 7 episodes
Clustering — 1× in this paper · explained in 2 episodes
Cosine Similarity — 1× in this paper · explained in 3 episodes
Domain Adaptation — 1× in this paper · explained in 5 episodes
Human-in-the-Loop — 1× in this paper · explained in 3 episodes
Latent Space — 1× in this paper · explained in 7 episodes
Out-of-Distribution (OOD) Detection — 1× in this paper · explained in 2 episodes
Representation Learning — 1× in this paper · explained in 2 episodes
Trace — 1× in this paper · explained in 2 episodes
Transformer — 1× in this paper · explained in 2 episodes