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GameHorizon Suite: Multi-Horizon Data and Evaluation in Gameplay

Paper recorded by Signals 4 on 2026-09-21 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-21 on arXiv · recorded by Signals 4 on 2026-09-22

Category: cs.AI · 人工智能 · first seen 2026-09-22

Abstract

Modern video games provide a measurable testbed for AI models, combining abilities of visual understanding, instruction decomposition, goal planning, and precise action control over multiple temporal horizons. Existing datasets and benchmarks, however, either cover a narrow range of games, lack language instructions, or rely on high-variance online rollouts. To address these challenges, we introdu

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#1 most recent of 340 cs.AI papers we have recorded · ↓ older: WorldCrafter: Consistent Video World Model with Implicit 3D-aware Memo
Cite this page: GameHorizon Suite: Multi-Horizon Data and Evaluation in Gameplay: the #1 most recent of 340 cs.AI papers we have recorded (as of 2026-09-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/gamehorizon-suite-multi-horizon-data-and-evaluation-in-gameplay.html
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