Tagged articles

online distillation

3 articles · Page 1 of 1

Sep 17, 2026 · Artificial Intelligence

LLM Post-Training Paradigm Shift: 5 New Paths Replacing Monolithic RL

This article analyzes five fundamental shifts in LLM post-training over the past six months: moving from monolithic RL to expert distillation (MOPD), online distillation as a 10x cheaper RL alternative, refined RLVR techniques addressing entropy collapse and exploration, SFT-RL distribution alignment, and data quality as an irrecoverable hard constraint.

LLM Post-TrainingMiMo-V2-FlashRLVR

0 likes · 9 min read

LLM Post-Training Paradigm Shift: 5 New Paths Replacing Monolithic RL

Model Perspective

Jul 31, 2026 · Artificial Intelligence

Understanding the Post-Training Process in DeepSeek V4‑Flash

DeepSeek released the V4‑Flash model with the same architecture as the preview but a revamped post‑training pipeline—SFT, reinforcement learning with GRPO, and distillation—yielding dramatic benchmark jumps and illustrating how post‑training now defines the model's real‑world capabilities.

DeepSeekGRPOLLM training

0 likes · 11 min read

Understanding the Post-Training Process in DeepSeek V4‑Flash

SuanNi

Mar 12, 2026 · Artificial Intelligence

How OpenClaw‑RL Turns Everyday Interactions into Self‑Evolving AI

OpenClaw‑RL, a new reinforcement‑learning framework from Princeton, captures hidden evaluative and instructional signals in daily user interactions, converts them into real‑time training data, and uses a decoupled asynchronous architecture with binary RL and online policy distillation to achieve superior performance in both personal‑device and cloud‑scale scenarios.

AI FeedbackAsynchronous ArchitectureSelf-evolution

0 likes · 10 min read

How OpenClaw‑RL Turns Everyday Interactions into Self‑Evolving AI