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Podcast: Arxiv Papers
Episode: L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning
Description: The paper introduces Length Controlled Policy Optimization (LCPO) for training reasoning models, enabling controlled output length and improved performance, outperforming existing methods while allowing for efficient compute allocation.https://arxiv.org/abs//2503.04697YouTube: https://www.youtube.com/@ArxivPapersTikTok: https://www.tiktok.com/@arxiv_papersApple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers