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cs.SE2025★ 1 cited
SEER: Self-Enhancing Chain-of-Thought Compression for Reasoning Models
Kerui Huang, Shuhan Liu, Xing Hu +3
Chain-of-Thought (CoT) prompting can substantially improve the reasoning ability of large language models (LLMs), but it often comes with high inference cost due to long and poorly…
cs.SE2025
FGIT: Fault-Guided Fine-Tuning for Code Generation
Lishui Fan, Zhongxin Liu, Haoye Wang +3
Modern instruction-tuned large language models (LLMs) have made remarkable progress in code generation. However, these LLMs fine-tuned with standard supervised fine-tuning (SFT) so…