腾讯混元推出 EvolveScaler，将世界定义为可执行状态机再渲染成自然语言，以模拟记录被撤回、修正、回填的"信息演化"过程。该基准含 117 个原型、159 个问题算子、5 个难度层级，单样本最多约 1200 个事件；14 个前沿模型在最难层级上 avg@5 中位数降至 11.3。用它训练则在 8 个分布外基准上平均提升 5.25。
🚀 EvolveScaler is here.
Read a 40-day RPG log. Now answer one question: if you skip the mini-boss on Day 7, do you still beat the final boss?
The answer isn't in the log. You have to replay the world.
That's Information Evolution — records get retracted, corrected, backfilled. The world keeps changing after you read it.
So we build it backwards: define the world as an executable state machine, then render it into natural language. Code guarantees the logic. Language delivers the mess.
➡️ 117 prototypes. 159 question operators. 5 difficulty tiers. Up to ~1,200 events per sample.
➡️ 14 frontier models, hardest tier: median avg@5 falls to 11.3.
➡️ Train on it instead: +5.25 average across 8 out-of-distribution benchmarks.
Check out our paper and project page.
📚 Paper: https://t.co/wmDPkSiwre
🏠 Project Page: https://t.co/Jt7UPkZtCp
来源：@TencentHunyuan · x.com