On July 3, 2026, a new paper published on ArXiv discusses innovative approaches to improving language models through reinforcement learning and self-distillation.
The study presents Reinforcement Learning with Verifiable Rewards (RLVR) and explores self-distillation variants, including one termed SDPO.
A key focus of the research is on updating policies based on evaluations from a verifier, which may lead to more effective language model performance.