The Frequency Confound in Language-Model Surprisal and Metaphor Novelty
Language-model (LM) surprisal is widely used as a proxy for contextual predictability and has been reported to correlate with metaphor novelty judgments. However, surprisal is tightly intertwined with lexical frequency. We explore this interaction on metaphor novelty ratings using two different word frequency measures. We analyse surprisal estimates from eight Pythia model sizes and 154 training checkpoints. Across settings, word frequency is a stronger predictor of metaphor novelty than surprisal. Across training stages, the surprisal--novelty association peaks at an early stage and then falls again, mirroring a similarly timed increase in the surprisal--frequency association. These resu...
| Authors | Omar Momen, Sina Zarrieß |
|---|---|
| Primary category | cs.CL |
| Published | 7 May 2026 |
| Last updated at source | 17 May 2026 |
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