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Autori principali: Arnold, Stefan, Gröbner, René
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2509.23204
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author Arnold, Stefan
Gröbner, René
author_facet Arnold, Stefan
Gröbner, René
contents Language Models, when generating prepositional phrases, must often decide for whether their complements functions as an instrumental adjunct (describing the verb adverbially) or an attributive modifier (enriching the noun adjectivally), yet the internal mechanisms that resolve this split decision remain poorly understood. In this study, we conduct a targeted investigation into Gemma-2 to uncover and control the generation of prepositional complements. We assemble a prompt suite containing with-headed prepositional phrases whose contexts equally accommodate either an instrumental or attributive continuation, revealing a strong preference for an instrumental reading at a ratio of 3:4. To pinpoint individual attention heads that favor instrumental over attributive complements, we project activations into the vocabulary space. By scaling the value vector of a single attention head, we can shift the distribution of functional roles of complements, attenuating instruments to 33% while elevating attributes to 36%.
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spellingShingle Steering Prepositional Phrases in Language Models: A Case of with-headed Adjectival and Adverbial Complements in Gemma-2
Arnold, Stefan
Gröbner, René
Computation and Language
Language Models, when generating prepositional phrases, must often decide for whether their complements functions as an instrumental adjunct (describing the verb adverbially) or an attributive modifier (enriching the noun adjectivally), yet the internal mechanisms that resolve this split decision remain poorly understood. In this study, we conduct a targeted investigation into Gemma-2 to uncover and control the generation of prepositional complements. We assemble a prompt suite containing with-headed prepositional phrases whose contexts equally accommodate either an instrumental or attributive continuation, revealing a strong preference for an instrumental reading at a ratio of 3:4. To pinpoint individual attention heads that favor instrumental over attributive complements, we project activations into the vocabulary space. By scaling the value vector of a single attention head, we can shift the distribution of functional roles of complements, attenuating instruments to 33% while elevating attributes to 36%.
title Steering Prepositional Phrases in Language Models: A Case of with-headed Adjectival and Adverbial Complements in Gemma-2
topic Computation and Language
url https://arxiv.org/abs/2509.23204