Large Model Pretraining and Fine‑Tuning: A 2026 Technical Guide from Scaling Laws to Post‑Training Revolution

This article explains the full lifecycle of large language models in 2026, covering pretraining fundamentals, the limits of classic Scaling Laws, data‑centric advances, fine‑tuning strategies, RLHF, DPO, and the emerging post‑training methods GRPO, DAPO and RLVR, with concrete benchmarks and cost analyses.

DAPODPOGRPO

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Large Model Pretraining and Fine‑Tuning: A 2026 Technical Guide from Scaling Laws to Post‑Training Revolution

Baobao Algorithm Notes

Jan 24, 2026 · Artificial Intelligence

What Advances Do GRPO, DAPO, GSPO, and SAPO Bring Over PPO?

After DPO, the typical research trajectory moves through GRPO, DAPO, GSPO, and SAPO, each introducing new optimization objectives, sampling strategies, and reward‑shaping techniques that aim to reduce memory usage, improve gradient stability, and enhance the efficiency of large‑model reinforcement learning.

DAPOGRPOGSPO

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What Advances Do GRPO, DAPO, GSPO, and SAPO Bring Over PPO?

Data Party THU

Sep 4, 2025 · Artificial Intelligence

Unraveling PPO Variants: From GRPO to DAPO and GSPO – A Deep Dive

This article provides a comprehensive technical analysis of PPO‑based reinforcement learning methods for large language models, detailing the evolution from the original PPO algorithm through GRPO, DAPO, and GSPO, and explaining their motivations, mathematical formulations, advantages, and practical challenges such as entropy collapse and importance‑sampling variance.

DAPOGRPOGSPO

0 likes · 30 min read

Unraveling PPO Variants: From GRPO to DAPO and GSPO – A Deep Dive