Sample-efficient active learning for materials informatics using integrated posterior variance

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A Foreword on AGENTS.md#One aspect of agents I hadn’t researched but knew was necessary to getting good results from agents was the concept of the AGENTS.md file: a file which can control specific behaviors of the agents such as code formatting. If the file is present in the project root, the agent will automatically read the file and in theory obey all the rules within. This is analogous to system prompts for normal LLM calls and if you’ve been following my writing, I have an unhealthy addiction to highly nuanced system prompts with additional shenanigans such as ALL CAPS for increased adherence to more important rules (yes, that’s still effective). I could not find a good starting point for a Python-oriented AGENTS.md I liked, so I asked Opus 4.5 to make one:

任命杨合庆为全国人民代表大会常务委员会法制工作委员会副主任。

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