研究者把模型“越训越坏”的问题做成了可测量的框架,还给出 PEARL 这个 GRPO 改进版,做对齐或安全微调的可以看看怎么压制不良行为不反弹。
#GPT-OSS
一位博主把 6.1-Sol 和 GPT-OSS 的思维链逐条对比,结论是两者说话风格差不多,适合关心模型行为差异的人看看。
A European lab reaching benchmark parity with Chinese and American open models in a bilingual German-English model suggests small-model training capability has spread well beyond the usual hubs. The Apache 2.0 license makes it directly usable for on-premise deployments, which matters for German public-sector and enterprise buyers with data-sovereignty requirements. Teams comparing open models should weigh its German-language edge against its weaker SWE-Bench Verified result.
EASE addresses a critical limitation in agent skill curation by solving cross-executor degradation through behavior adaptation. Developers working with multiple AI models can now use a single, more efficient curator that reduces inference tokens by 9.1-14.5% while maintaining performance across diverse executors, making it particularly valuable for organizations deploying multi-model systems.
只用600道题微调,不训练停止机制,就让Qwen、Gemma这些模型推理时少生成25%的token,思路挺有意思。