NVIDIA Polar explained: training AI coding agents with token-faithful GRPO
NVIDIA Polar explained: training AI coding agents with token-faithful GRPO – Reinforcement learning for language models hit a wall nobody talks about enough. Not the data wall, not the compute wall. The integration wall. You have a sophisticated agent harness — something that took months to build, tuned for specific tool schemas, context policies, multi-agent orchestration — and you want to run RL on top of it. Standard frameworks tell you to rewrite everything behind their interfaces. Most teams give up or ship a half-baked version that loses critical training signals along the way.
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