Community size rather than grammatical complexity better predicts Large Language Model accuracy in a novel Wug Test

ArXi:2510.12463v3 Announce Type: replace The linguistic abilities of Large Language Models are a matter of ongoing debate. This study contributes to this discussion by investigating model performance in a morphological generalization task that involves novel words. Using a multilingual adaptation of the Wug Test, six models were tested across four partially unrelated languages (Catalan, English, Greek, and Spanish) and compared with human speakers.