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cs.LG2026
From Weeks to Hours: Fast and Principled SFT Data Generation for Reasoning LLMs
Hongyi Henry Jin, Wenhan Yang, Meysam Ghaffari +2
Reasoning-oriented post-training enables large language models (LLMs) to solve complex tasks via multi-step inference. Supervised fine-tuning (SFT) on high-quality reasoning traces…
cs.LG2026
Reasoning Quality Emerges Early: Data Curation for Reasoning Models
Hongyi Henry Jin, Wenhan Yang, Meysam Ghaffari +2
Supervised fine-tuning (SFT) on a small, high-quality set of long reasoning traces is an effective approach for eliciting strong reasoning capabilities in Large Language Models (LL…