Visual agents need to coordinate reasoning and action while their environment evolves during inference. We introduce LOLPlay, a benchmark in native League of Legends with 36 champion-specific tasks sp
LOLPlay evaluates visual agents on real-time League of Legends tasks, finding that increased reasoning effort does not improve success and can reduce interaction time.
Visual agents need to coordinate reasoning and action while their environment evolves during inference. We introduce LOLPlay, a benchmark in native League of Legends with 36 champion-specific tasks spanning resource management, combat, cooperation, and objectives. Agents interact through screenshots and mouse--keyboard actions; automated initialization and 82 executable subgoal checks distinguish partial progress from completion. Across 324 task evaluations of three models at three reasoning-effort settings, 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. However, high effort improves…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
LOLPlay: Benchmarking Real-Time Visual Agents in League of Legends was first seen on Hugging Face · Daily papers on Nov 4, 2026. Since then it has appeared in 9 checks on 2 different days. Its best position was #27 of 30, reached on Nov 5, 03:28 UTC. It dropped off the list after Nov 5, 03:28 UTC.
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Not at the moment. It was last on the list on Nov 5, 03:28 UTC, after 2 days of trending.
#27 on Hugging Face · Daily papers, on Nov 5, 03:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Nov 4, 2026 and has been on the list on 2 days (9 checks) since.