Paper

Post-training is (Massive) Supervised Learning

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arXiv:2606. 07527v1 Announce Type: new Abstract: The prevailing paradigm for training LLMs has evolved to rely on a massive post-training phase consisting of SFT and RL.

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Authors: Michael Hassid, Yossi Adi, Roy Schwartz
Released: 2026-06-09 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because Post-training is (Massive) Supervised Learning overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: code, eval, rate, compare, trained, position, model. Source: arxiv cs.CL (NLP).
arXiv: 2606.07527

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