Flash-BoN Also Accelerates Post-Training
RisingSayak · x · 2026-07-14
The author adds that the "cheap candidate generation" in Flash-BoN is useful not only for test-time scaling but also for accelerating RL post-training.
They share their results: Flash-Flow-GRPO achieves the convergence of the baseline Flow-GRPO in 10× fewer steps. In the replies, the author also notes that Flash-BoN can be combined with other methods and is entirely complementary.
Related event: Flash-BoN: A Stronger Baseline for Diffusion Inference and Post-Training(7 posts)→
More from Research
- New survey maps how agentic systems are learning to improve themselves — SchmidhuberAI · 2026-07-21
- Jacob Tsimerman interview frames LLMs as a turning point for mathematical discovery — stevenstrogatz · 2026-07-21
- New survey bridges continual learning and parameter-efficient fine-tuning — v_lomonaco · 2026-07-21
- Daniel Hanchen’s 2-hour workshop covers open models, reward hacking and RL — danielhanchen · 2026-07-21
- Codex’s claimed proof of a math problem turns into a “CEO of math” meme — builderjaydub · 2026-07-21
- Tau Ceti launches as an AI-formalized mathematics library for Lean — wellecks · 2026-07-21