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Not exactly sure what you are looking for here.

That GRPO works?

> Group Relative Policy Optimization (GRPO), a variant reinforcement learning (RL) algorithm of Proximal Policy Optimization (PPO) (Schulman et al., 2017). GRPO foregoes the critic model, instead estimating the baseline from group scores, significantly reducing training resources. By solely using a subset of English instruction tuning data, GRPO obtains a substantial improvement over the strong DeepSeekMath-Instruct, including both in-domain (GSM8K: 82.9% → 88.2%, MATH: 46.8% → 51.7%) and out-of-domain mathematical tasks (e.g., CMATH: 84.6% → 88.8%) during the reinforcement learning phase

Page 2 of https://arxiv.org/pdf/2402.03300

That GRPO on code works?

> Similarly, for code competition prompts, a compiler can be utilized to evaluate the model’s responses against a suite of predefined test cases, thereby generating objective feedback on correctness

Page 4 of https://arxiv.org/pdf/2501.12948





None of those are novel domains w/ their own novel syntax & semantic validators, not to mention the dearth of readily available sources of examples for sampling the baselines. So again, where does it say it works for a programming language with nothing but a grammar & a compiler?

To quote you:

> here is no RL for programming languages.

and

> Either RL works & you have evidence

This is just so completely wrong, and here is the evidence.

I think everyone in this thread is just surprised you don't seem to know this.

Haven't you seen the hundreds of job ads for people to write code for LLMs to train on?


You're not going to get less confused by doubling down. None of your claims are valid & this is because you haven't actually tried to do what you're suggesting. Taking a grammar & compiler & RLing will get you nowhere.



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