This digest covers fine-tuning and post-training news from 2026-10-16 through 2026-10-27: eight new arXiv papers, two Hugging Face blog posts with reproducible SFT/GRPO recipes, and a new post-training product launch from Together AI.

🔥 Highlights

Welcome Beam: a 501B open model you can own, customize, and scale — direct LoRA-vs-full-parameter GRPO numbers on a 501B model.

Is it RL or Data? A Controlled Comparison of GRPO and Rejection-Sampling Fine-Tuning — GRPO beats RFT even after a 27-run tuning sweep for the baseline.

ECHO: Emergent Common-Mode Hidden Offsets Drive Vocabulary Collapse in Preference Optimization — a hidden signal that warns of DPO/SimPO collapse before it happens.

Turning Database Grading into RL Rewards: Post-Training Agents with ThinkingBox — deterministic reward engineering cuts RL cost per task by 3x.

Together Post-Training: frontier-grade model shaping, the way that fits you — a managed service with cookbooks for SFT, GRPO, DPO, and multi-LoRA serving.

arXiv

Mechanistic…