The authors developed frontier learning, an online curriculum for reinforcement learning with verifiable rewards.
Generating frontier-level problems improves reinforcement learning for LLM reasoning
An online curriculum uses procedural generators and regret-guided search to keep training problems aligned with a model’s changing capabilities.
Academic
Robin Faro · Shyam Sundhar Ramesh · Ilija Bogunovic · Aurelien Lucchi
University of Basel · University College London
Research Digest··2 min read
Faro et al.
Why this paper
From University of Basel and University College London
In one line
LLM reasoners improve by continually generating training problems at the edge of their evolving capability rather than using a fixed problem pool.
What we could check
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