Work

LLMs Out-of-the-Box Do Not Generate Context-Appropriate Word Order in Russian

Year: 2026

Type: conference-paper

Abstract: In this paper, we examine whether LLMs can generate context-appropriate word order in Russian.Using a new corpus of movie scripts in Russian, with a particular focus on dialogues, we investigate how various semantic, morphosyntactic, and discourse features influence word order choice.We show that traditional machine learning can use these features to model different word order fairly well.We also examine whether LLM dialogue partners can generate context-appropriate word order in Russian.With both zero-and few-shot prompting, LLMs fail to generate word orders beyond the default subject-verb-object.Instead, in order to generate context-appropriate word orders, LLMs need to be fine-tuned or given explicit word order suggestions from a traditional machine learning method.

Source: Annual Meeting of the Special Interest Group on Discourse and Dialogue

DOI: 10.18653/v1/2026.sigdial-1.32

Authors: Alina Shabaeva, John Frederick Bailyn, Owen Rambow

Institution: Stony Brook University

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: Stony Brook University

OpenAlex ID: W7214047224

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