cross-lingual-transfer

This paper studies cross-lingual transfer for machine translation among five Turkic languages using pairwise transfer matrices with mT5, finding that transfer is strongest between closely related pairs and that Latinization helps in script-mismatched settings.

This paper presents a systematic study of cross-lingual transfer for biomedical machine translation into low-resource Arabic-script languages, using Arabic and Persian as pivots. The authors evaluate LoRA adapter merging as a zero-data transfer strategy, showing it works surprisingly well for closely related languages like Dari.

This paper addresses the uncontrolled latent variable of transcription style in ASR models by introducing a method using coverage-aware decoder task tokens to enable controllable verbatim transcription with accurate word-level timing, achieving high disfluency detection F1 via zero-shot cross-lingual transfer.

This paper introduces KyrgyzLLM-Bench, a benchmark suite for evaluating large language models in the Kyrgyz language, comprising both natively authored and translated datasets, and provides a systematic evaluation of 26 models.

Presents Tatoxa, a state-of-the-art system for text detoxification in the Tatar language, outperforming existing LLMs. Introduces a new dataset and shows that cross-lingual transfer performs worse than native data.

This paper proposes a benchmark suite grounded in Pāṇinian grammar to unify Indic language processing across languages, aiming to improve accuracy, data efficiency, and transferability.

This paper empirically compares several LoRA variants for multilingual instruction tuning and finds no significant advantage of complex variants over basic LoRA in balancing cross-lingual transfer and knowledge retention.

This paper introduces PyLang, a programming language absent from all pretraining corpora, and shows that LLMs fine-tuned on it can learn syntax but fail to transfer algorithmic reasoning, resulting in an 'implementation fidelity gap' where models understand algorithms but cannot express them in an unfamiliar language.