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cs.CL2026
Diagnosing On-Policy Self-Distillation for Reasoning Language Models
Yang Li, Gongle Xue, Yuheng Yuan +4
On-policy self-distillation (OPSD) has attracted growing interest as a promising approach to improve the reasoning ability of language models. Without external rewards nor a separa…
cs.CL2024
I-SHEEP: Self-Alignment of LLM from Scratch through an Iterative Self-Enhancement Paradigm
Yiming Liang, Ge Zhang, Xingwei Qu +9
Large Language Models (LLMs) have achieved significant advancements, however, the common learning paradigm treats LLMs as passive information repositories, neglecting their potenti…
cs.CL2024★ 2 cited
TEGEE: Task dEfinition Guided Expert Ensembling for Generalizable and Few-shot Learning
Xingwei Qu, Yiming Liang, Yucheng Wang +10
Large Language Models (LLMs) exhibit the ability to perform in-context learning (ICL), where they acquire new tasks directly from examples provided in demonstrations. This process…