Releases a 457-sentence Komi-Yazva--Russian parallel corpus and shows that retrieval-based few-shot prompting improves LLM translation over zero-shot in this low-resource setting, with performance varying by model and metric.
Machine Translation with Large Language Models: Prompting, Few-shot Learning, and Fine-tuning with QL o RA
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Automatic evaluation tools for literary translations correlate poorly with expert human judgments on creativity and exhibit bias favoring machine-translated texts.
A post-hoc framework using fertility and entropy from word alignments on reference translations shows context redistributes responsibility to context tokens for function words but not content words across three language pairs.
Benign multilingual fine-tuning causes language-specific safety drifts with adversarial compliance rates rising up to four-fold, decoupled from capability gains.
citing papers explorer
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A Komi-Yazva--Russian Parallel Corpus and Evaluation Protocol for Zero- and Few-Shot LLM Translation
Releases a 457-sentence Komi-Yazva--Russian parallel corpus and shows that retrieval-based few-shot prompting improves LLM translation over zero-shot in this low-resource setting, with performance varying by model and metric.
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Creativity Bias: How Machine Evaluation Struggles with Creativity in Literary Translations
Automatic evaluation tools for literary translations correlate poorly with expert human judgments on creativity and exhibit bias favoring machine-translated texts.
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Which Tokens Need Context? A Reference-Based Analysis of Translation Responsibility Using Fertility and Entropy
A post-hoc framework using fertility and entropy from word alignments on reference translations shows context redistributes responsibility to context tokens for function words but not content words across three language pairs.
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The Heterogeneous Safety Impacts of Benign Multilingual Fine-Tuning
Benign multilingual fine-tuning causes language-specific safety drifts with adversarial compliance rates rising up to four-fold, decoupled from capability gains.