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Investigating Syntactic Biases in Multilingual Transformers with RC Attachment Ambiguities in Italian and English

Published: April 14, 2025 | arXiv ID: 2504.09886v1

By: Michael Kamerath, Aniello De Santo

Potential Business Impact:

Computers don't understand sentences like people do.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

This paper leverages past sentence processing studies to investigate whether monolingual and multilingual LLMs show human-like preferences when presented with examples of relative clause attachment ambiguities in Italian and English. Furthermore, we test whether these preferences can be modulated by lexical factors (the type of verb/noun in the matrix clause) which have been shown to be tied to subtle constraints on syntactic and semantic relations. Our results overall showcase how LLM behavior varies interestingly across models, but also general failings of these models in correctly capturing human-like preferences. In light of these results, we argue that RC attachment is the ideal benchmark for cross-linguistic investigations of LLMs' linguistic knowledge and biases.

Page Count
16 pages

Category
Computer Science:
Computation and Language