8 citations · 13 across the 11 of their papers we have counts for
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cs.AI2026
Purified OPSD: On-Policy Self-Distillation Without Losing How to Think
Zhanming Shen, Jintao Tong, Shaotian Yan +9
On-policy self-distillation (OPSD) has emerged as a promising paradigm for improving LLM reasoning, where a privileged teacher with access to reference solutions provides token-lev…
cs.AI2023★ 8 cited
Maybe Only 0.5% Data is Needed: A Preliminary Exploration of Low Training Data Instruction Tuning
Hao Chen, Yiming Zhang, Qi Zhang +5
Instruction tuning for large language models (LLMs) has gained attention from researchers due to its ability to unlock the potential of LLMs in following instructions. While instru…