腾讯混元发布科学发现智能体 Hyra
腾讯混元发布科学发现智能体 Hyra,采用 Context Agent 维护经验库、多个 Proposal Agent 生成并沙盒评估 solution 的异步流水线,无评估器时升级为双层循环让评估器与 solution 共进化。在 NanoChat Autoresearch、NanoGPT Speedrun 和 SOL-ExecBench 三项任务上,Hyra-1.0 分别取得 Validation BPB 0.9015、Time to 3.28 loss 76.4s 和 Mean SOL 0.771,均超过 Recursive 报告的结果。在 55 个数学开放问题中,Hyra 于 29 个上刷新历史最好结果,相关结果已在 GitHub 开源。
/ Royal Observatory of Belgium, Monthly Mean Total Sunspot Number ,本文太阳黑子实验所使用的历史月度数据来源:https://www.sidc.be/SILSO/infosnmtot [^ref13]: 相关论文: Can Language Models Discover Scaling Laws ,其中讨论了从训练观测中发现 scaling law 的自动化方法:https://arxiv.org/abs/2507.21184 [^ref14]: AdderBoard ,面向神经网络加法任务的公开参数效率榜单与实现仓库:https://github.com/anadim/AdderBoard [^ref15]: Gushu Li、Yufei Ding 与 Yuan Xie, “Tackling the Qubit Mapping Problem for NISQ-Era Quantum Devices” ,提出 SABRE 量子比特映射与路由方法:https://arxiv.org/abs/1809.02573 [^
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