Stress-Testing LLMs With Reasoning Gym: Building & Training a Multi-step Reasoning Task
Published:
I’ve been exploring how far reinforcement-learning paradigms can push large language models when the reward is verifiable reasoning correctness. That led me to (i) extending Reasoning Gym with a procedurally-generated, multi-hop puzzle set that forces deduction ↔ induction ↔ abduction ↔ transduction hand-offs, (ii) wiring it into the TRL training loop, and (iii) seeing what the first accuracy curves look like. Below is the why, the how, and the initial results.