{"slug": "prorl-prolonged-rl-expands-reasoning-boundaries-interactive-visual-explainer", "title": "ProRL: Prolonged RL Expands Reasoning Boundaries — interactive visual explainer | Rudrite Research", "summary": "Researchers Liu et al. published a paper on arXiv 2025 introducing ProRL, a method using prolonged reinforcement learning with KL resets to expand reasoning boundaries in AI models. An interactive visual explainer of the paper is available online.", "body_md": "# ProRL: Prolonged RL Expands Reasoning Boundaries\n\nProlonged RL with KL resets expands what a reasoning model can do, not just sharpens it.\n\nLiu et al. · arXiv 2025 · Reasoning & RL. [Read the paper ↗](https://arxiv.org/abs/2505.24864)\n\nA free, interactive, animated visual explainer of ProRL: Prolonged RL Expands Reasoning Boundaries — every exhibit computed from the real formulas, with verbatim quotes from the source.\n\n## Questions\n\n- What is ProRL: Prolonged RL Expands Reasoning Boundaries?\n- Prolonged RL with KL resets expands what a reasoning model can do, not just sharpens it.\n- Who published ProRL: Prolonged RL Expands Reasoning Boundaries, and where?\n- Liu et al. — arXiv 2025 (arXiv:2505.24864).\n- Where can I find a visual explainer of ProRL: Prolonged RL Expands Reasoning Boundaries?\n- Right here — a free, interactive, animated walkthrough of the whole paper, with exhibits computed from the real formulas and verbatim quotes from the source.\n\n## Related explainers\n\n[DeepSeek-R1](/deepseek-r1)[Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](/chain-of-thought)[Training language models to follow instructions with human feedback](/instructgpt)[Direct Preference Optimization: Your Language Model is Secretly a Reward Model](/dpo)[DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](/deepseekmath)[Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters](/test-time-compute)[Constitutional AI: Harmlessness from AI Feedback](/constitutional-ai)[DAPO: An Open-Source LLM Reinforcement Learning System at Scale](/dapo)", "url": "https://wpnews.pro/news/prorl-prolonged-rl-expands-reasoning-boundaries-interactive-visual-explainer", "canonical_source": "https://research.rudrite.com/prorl", "published_at": "2026-06-13 00:00:00+00:00", "updated_at": "2026-06-14 18:18:14.629537+00:00", "lang": "en", "topics": ["machine-learning", "ai-research", "large-language-models", "ai-agents"], "entities": ["Liu et al.", "arXiv", "ProRL", "DeepSeek-R1", "Chain-of-Thought Prompting", "InstructGPT", "Direct Preference Optimization", "Constitutional AI"], "alternates": {"html": "https://wpnews.pro/news/prorl-prolonged-rl-expands-reasoning-boundaries-interactive-visual-explainer", "markdown": "https://wpnews.pro/news/prorl-prolonged-rl-expands-reasoning-boundaries-interactive-visual-explainer.md", "text": "https://wpnews.pro/news/prorl-prolonged-rl-expands-reasoning-boundaries-interactive-visual-explainer.txt", "jsonld": "https://wpnews.pro/news/prorl-prolonged-rl-expands-reasoning-boundaries-interactive-visual-explainer.jsonld"}}