Full Parameter Support: Because the final shortcut refinement (Step 3 above) uses A* on detailed maps within each cluster, all your specified parameters are naturally incorporated:
同时，公司宣布任命吴亦泓女士及萧杨女士为新任独立董事。此项任命旨在保持董事会多元化的专业知识与创新视角。吴亦泓现任MakeMyTrip、阿里巴巴健康、太古地产及诺亚控股等多家上市公司独立董事，曾任如家酒店集团首席战略官及首席财务官。萧杨曾任职于Capital International Investors、Principal Global Investors及平安资产管理有限公司，担任投资分析师及投资组合经理等职。
，更多细节参见新收录的资料
all you’ll do is get inconvenienced.。新收录的资料对此有专业解读
Such pressure may be a strategy to put Cuba in a weaker position at the negotiating table.，这一点在新收录的资料中也有详细论述
Abstract:Large language model (LLM)-powered agents have demonstrated strong capabilities in automating software engineering tasks such as static bug fixing, as evidenced by benchmarks like SWE-bench. However, in the real world, the development of mature software is typically predicated on complex requirement changes and long-term feature iterations -- a process that static, one-shot repair paradigms fail to capture. To bridge this gap, we propose \textbf{SWE-CI}, the first repository-level benchmark built upon the Continuous Integration loop, aiming to shift the evaluation paradigm for code generation from static, short-term \textit{functional correctness} toward dynamic, long-term \textit{maintainability}. The benchmark comprises 100 tasks, each corresponding on average to an evolution history spanning 233 days and 71 consecutive commits in a real-world code repository. SWE-CI requires agents to systematically resolve these tasks through dozens of rounds of analysis and coding iterations. SWE-CI provides valuable insights into how well agents can sustain code quality throughout long-term evolution.