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Adamergex: Cross-lingual transfer with large language models via adaptive adapter merging
As an effective alternative to the direct fine-tuning on target tasks in specific languages,
cross-lingual transfer addresses the challenges of limited training data by decoupling''task …
cross-lingual transfer addresses the challenges of limited training data by decoupling''task …
Transcending language boundaries: Harnessing llms for low-resource language translation
Large Language Models (LLMs) have demonstrated remarkable success across a wide
range of tasks and domains. However, their performance in low-resource language …
range of tasks and domains. However, their performance in low-resource language …
Revolutionising translation with AI: Unravelling neural machine translation and generative pre-trained large language models
SC Siu - New advances in translation technology: Applications …, 2024 - Springer
This work explores the technical advancements in artificial intelligence (AI) for translation,
with a focus on neural machine translation (NMT) and large language models (LLMs) as …
with a focus on neural machine translation (NMT) and large language models (LLMs) as …
LCS: A language converter strategy for zero-shot neural machine translation
Multilingual neural machine translation models generally distinguish translation directions
by the language tag (LT) in front of the source or target sentences. However, current LT …
by the language tag (LT) in front of the source or target sentences. However, current LT …
Languages transferred within the encoder: On representation transfer in zero-shot multilingual translation
Understanding representation transfer in multilingual neural machine translation can reveal
the representational issue causing the zero-shot translation deficiency. In this work, we …
the representational issue causing the zero-shot translation deficiency. In this work, we …
Transformer-Based Amharic-to-English Machine Translation with Character Embedding and Combined Regularization Techniques
Amharic is the working language of Ethiopia and, owing to its Semitic characteristics, the
language is known for its complex morphology. It is also an under-resourced language …
language is known for its complex morphology. It is also an under-resourced language …
Improving multilingual neural machine translation by utilizing semantic and linguistic features
The many-to-many multilingual neural machine translation can be regarded as the process
of integrating semantic features from the source sentences and linguistic features from the …
of integrating semantic features from the source sentences and linguistic features from the …
How Multilingual Are Large Language Models Fine-Tuned for Translation?
A new paradigm for machine translation has recently emerged: fine-tuning large language
models (LLM) on parallel text has been shown to outperform dedicated translation systems …
models (LLM) on parallel text has been shown to outperform dedicated translation systems …
Learning multilingual sentence representations with cross-lingual consistency regularization
Multilingual sentence representations are the foundation for similarity-based bitext mining,
which is crucial for scaling multilingual neural machine translation (NMT) system to more …
which is crucial for scaling multilingual neural machine translation (NMT) system to more …
An empirical study of consistency regularization for end-to-end speech-to-text translation
Consistency regularization methods, such as R-Drop (Liang et al., 2021) and CrossConST
(Gao et al., 2023), have achieved impressive supervised and zero-shot performance in the …
(Gao et al., 2023), have achieved impressive supervised and zero-shot performance in the …