Predicting Emerging Topics from Outliers: A Prospective Study of Weak Signals in Embedding Space

arXiv:2609.29183 · cs.CL · Submitted 2026-09-24 · Read on arXiv

cs.CL

Submitted: 2026-09-24

Updated: 2026-09-24

Code: https://github.com/evangeliazve/aacl-p

Terminology

Clustering — 11× in this paper · explained in 2 episodes
Ablation — 10× in this paper · explained in 1 episode
Trace — 5× in this paper · explained in 2 episodes
Alignment — 4× in this paper · explained in 1 episode
Embeddings — 4× in this paper · explained in 2 episodes
Robustness — 4× in this paper · explained in 5 episodes
F1 Score — 3× in this paper · explained in 3 episodes
Interpretability — 3× in this paper · explained in 15 episodes
SHAP values — 3× in this paper · explained in 2 episodes
Calibration — 2× in this paper · explained in 7 episodes
External Validation — 2× in this paper · explained in 2 episodes
Ablation study — 1× in this paper · explained in 1 episode
Actor — 1× in this paper · explained in 3 episodes
Adaptation — 1× in this paper · explained in 1 episode
Data Provenance — 1× in this paper · explained in 2 episodes
Provenance — 1× in this paper · explained in 4 episodes
Regularization — 1× in this paper · explained in 3 episodes
Transferability — 1× in this paper · explained in 4 episodes

Sources

BERTopic: Neural topic modeling with a class-based TF-IDF procedure

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