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cs.CL2024
Multilingual Large Language Models: A Systematic Survey
Shaolin Zhu, Supryadi, Shaoyang Xu +7
This paper provides a comprehensive survey of the latest research on multilingual large language models (MLLMs). MLLMs not only are able to understand and generate language across…
cs.CL2024
Efficiently Exploring Large Language Models for Document-Level Machine Translation with In-context Learning
Menglong Cui, Jiangcun Du, Shaolin Zhu +1
Large language models (LLMs) exhibit outstanding performance in machine translation via in-context learning. In contrast to sentence-level translation, document-level translation (…
cs.CL2024
A Comprehensive Evaluation of Quantization Strategies for Large Language Models
Renren Jin, Jiangcun Du, Wuwei Huang +4
Increasing the number of parameters in large language models (LLMs) usually improves performance in downstream tasks but raises compute and memory costs, making deployment difficul…