{"version":1,"type":"story","url":"https://digestai.news/story/lolplay-introduces-benchmark-for-realtime-visual-agents-in-league-of-l","json":"https://digestai.news/story/lolplay-introduces-benchmark-for-realtime-visual-agents-in-league-of-l.json","markdown":"https://digestai.news/story/lolplay-introduces-benchmark-for-realtime-visual-agents-in-league-of-l.md","slug":"lolplay-introduces-benchmark-for-realtime-visual-agents-in-league-of-l","headline":"LOLPlay introduces benchmark for real‑time visual agents in league of legends","summary":"LOLPlay benchmark includes 36 champion‑specific tasks and 82 subgoal checks in League of Legends.\n\nThe authors evaluate three models across three reasoning‑effort settings on 324 task instances. GPT‑6 Astra achieves the highest task success rate of 25.0 % at low and medium effort, and the highest subgoal success rate of 40.3 % at medium effort. Higher reasoning effort does not improve performance for any model, and longer requests reduce interaction rounds for Astra.\n\nTrajectory analysis shows incomplete subgoal composition and actions executed after scene changes, highlighting a need for agents that combine visual reasoning with timely action.","keyPoints":["LOLPlay benchmark includes 36 champion‑specific tasks and 82 subgoal checks in League of Legends.","GPT‑6 Astra tops the benchmark with 25.0 % task success at low/medium effort and 40.3 % subgoal success at medium effort.","Higher reasoning effort does not improve performance, and longer requests reduce interaction rounds for Astra."],"whyItMatters":"The benchmark provides a realistic testbed for visual agents that must reason and act in real‑time game environments, revealing gaps in current models and guiding future research toward more timely, coordinated AI behavior.","category":{"slug":"research","name":"Research","url":"https://digestai.news/category/research"},"entities":{"companies":[],"models":["GPT-6 Astra"],"people":[]},"firstPublishedAt":"2026-11-04T05:00:00Z","updatedAt":"2026-11-04T05:00:00Z","sourceCount":1,"hasPrimarySource":true,"sources":[{"outlet":"arXiv cs.AI","title":"LOLPlay: Benchmarking Real-Time Visual Agents in League of Legends","url":"https://arxiv.org/abs/2611.03685","publishedAt":"2026-11-04T05:00:00Z","type":"primary","primary":true,"lead":true}],"sourceNotes":null,"discussions":[],"thread":null,"cite":{"text":"Digest AI, \"LOLPlay introduces benchmark for real‑time visual agents in league of legends\", 4 November 2026, https://digestai.news/story/lolplay-introduces-benchmark-for-realtime-visual-agents-in-league-of-l","publisher":"Digest AI","title":"LOLPlay introduces benchmark for real‑time visual agents in league of legends","datePublished":"2026-11-04T05:00:00Z","url":"https://digestai.news/story/lolplay-introduces-benchmark-for-realtime-visual-agents-in-league-of-l"},"generatedBy":"Written by Digest AI's editorial model from the linked sources; the sources are the record.","license":"Headlines, digests and key points are written by Digest AI and may be quoted with a link to the story page. Linked articles belong to their publishers. Terms: https://digestai.news/terms#reuse"}