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cs.CL2025
MARCO: Meta-Reflection with Cross-Referencing for Code Reasoning
Yusheng Zhao, Xiao Luo, Weizhi Zhang +4
The ability to reason is one of the most fundamental capabilities of large language models (LLMs), enabling a wide range of downstream tasks through sophisticated problem-solving.…
cs.CL2025
Semi-supervised Fine-tuning for Large Language Models
Junyu Luo, Xiao Luo, Xiusi Chen +3
Supervised fine-tuning (SFT) is crucial in adapting large language model (LLMs) to a specific domain or task. However, only a limited amount of labeled data is available in practic…
cs.CL2024
RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response
Junyu Luo, Xiao Luo, Kaize Ding +3
Supervised fine-tuning (SFT) plays a crucial role in adapting large language models (LLMs) to specific domains or tasks. However, as demonstrated by empirical experiments, the coll…