2 papers
cs.SE2026
An Empirical Study on Influence-Based Pretraining Data Selection for Code Large Language Models
Chengli Xing, Zhengran Zeng, Gexiang Fang +3
Recent advancements in code large language models (Code-LLMs) have demonstrated remarkable capabilities in resolving programming related tasks. Meanwhile, researchers have recogniz…
cs.CL2025
ReGenesis: LLMs can Grow into Reasoning Generalists via Self-Improvement
Xiangyu Peng, Congying Xia, Xinyi Yang +3
Post-training Large Language Models (LLMs) with explicit reasoning trajectories can enhance their reasoning abilities. However, acquiring such high-quality trajectory data typicall…