analiza aiqbench
Alibaba's QwenGyre represents a significant advancement in training coding agents for extreme-long-horizon tasks, utilizing an elastic reinforcement learning framework to handle rollouts of up to one million tokens without modifying the underlying harness. This development directly addresses scalability challenges in agent-based systems by optimizing resource efficiency during extended inference periods.
Alibaba Qwen Introduces QwenGyre: Elastic Reinforcement Learning RL for XLong-Horizon Agents
Alibaba’s Qwen team has introduced QwenGyre, an elastic reinforcement learning RL framework for extreme-long-horizon agent training. QwenGyre is an online reinforcement learning system from Alibaba that trains coding agents through unmodified, black-box harnesses. It targets rollouts that run for hours and process close to 1M tokens. The QwenGyre elastic RL framework was used on Qwen’s […] The post Alibaba Qwen Introduces QwenGyre: Elastic Reinforcement Learning RL for XLong-Horizon Agents appeared first on MarkTechPost.
Citește articolul complet pe MarkTechPostSubiecte conexe
QwenGyre: An Elastic Reinforcement Learning Framework for Training xLong-Horizon Agents
arXiv · 30 sept. 2026

[AINews] Meta Muse Wonder & Wonder Full: MSL’s Claude 5.5-tier Frontier Model
Latent Space · 13 oct. 2026

[AINews] Reality Checks on AI News (Yegge shuts down Gas Town, Databricks’ +60% Astra cost)
Latent Space · 17 sept. 2026

[AINews] Muse Spark 1.3 matches GPT-5.6-Sol, confirming Meta Superintelligence as the newest Frontier Lab, >90% discount for training
Latent Space · 3 sept. 2026