arXiv Computation and Language By Sangwoo Kim, Sangah Lee

How Do Language Models Represent and Use Phonological Information for Allomorph Selection?

Read the original on arXiv Computation and Language →

Language models trained on tokenized text still reliably produce morphemes whose form depends on phonology, but it was unclear whether this relies on memorization or rule-like generalization. The study shows that for the English indefinite article a/an, the phonological condition is encoded along a single linear direction in trigger-token embeddings, causally drives article selection in token-level wug tests, and is used by the model to forecast the upcoming trigger token’s phonological feature for article choice. The authors further investigate whether this rule-like generalization extends to allomorph selection in other languages and to explicit phonological judgment, offering a mechanistic account that separates generation-time ability from metalinguistic judgments.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

arXiv Computation and Language
Sep 3

Disentangling Statistical Preemption from Entrenchment in Language Models' Avoidance of Overgeneralization

The paper investigates how language models avoid overgeneralizations by distinguishing between two types of indirect negative evidence: preemption and entrenchment. Through controlled rearing experiments on models trained on child‑caregiver conversations, the authors find that models do not exhibit verb‑specific preemption but show weak abstract preemption. Analysis of training dynamics suggests that competing structures act as indirect positive evidence rather than negative in the verb‑specific condition.

By Yixuan Wang, Freda Shi, Kanishka Misra
arXiv AI
5d ago

Patterns of Priming in Production: Lexical, Semantic and Structural Alignment in Language Model Generation

The paper studies structural priming in language model production by conducting controlled sentence‑completion experiments on dative constructions. Results show that language models exhibit priming effects, especially when sentences are semantically coherent, with stronger relative increases for double‑object datives and larger absolute increases for prepositional‑object datives. The study also finds that primed completions involve more lexico‑semantic repetition, indicating that priming operates across syntactic, lexical, and semantic levels.

By Giulia Pucci, Ruizhe Li, Arabella Sinclair