miniTE: Diagnosing and Bridging the Execution Gap in Native NVFP4 Reinforcement Learning
arXiv:2610.23928v1 Announce Type: new Abstract: Native NVFP4 promises to accelerate reinforcement learning (RL) for large language models (LLMs), but achieving stable learning across separate training and sampling engines remains challenging. We show that matching model weights and numerical format…
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- 2026-10-20 04:00 · arXiv cs.LG
miniTE: Diagnosing and Bridging the Execution Gap in Native NVFP4 Reinforcement Learning