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cs.CL2025
CYCLE-INSTRUCT: Fully Seed-Free Instruction Tuning via Dual Self-Training and Cycle Consistency
Zhanming Shen, Hao Chen, Yulei Tang +6
Instruction tuning is vital for aligning large language models (LLMs) with human intent, but current methods typically rely on costly human-annotated seed data or powerful external…
cs.CL2025
FuxiMT: Sparsifying Large Language Models for Chinese-Centric Multilingual Machine Translation
Shaolin Zhu, Tianyu Dong, Bo Li +1
In this paper, we present FuxiMT, a novel Chinese-centric multilingual machine translation model powered by a sparsified large language model (LLM). We adopt a two-stage strategy t…