Scalable machine learning models for predicting quantum transport in disordered 2D hexagonal materials

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Initially I aimed to test with at least 10 formulas for each model for SAT/UNSAT, but it turned out to be more expensive than I expected, so I tested ~5 formulas for each case/model. First, I used the openrouter API to automate the process, but I experienced response stops in the middle due to long reasoning process, so I reverted to using the chat interface (I don't if this was a problem from the model provider or if it's an openrouter issue). For this reason I don't have standard outputs for each testing, but I linked to the output for each case I mentioned in results.

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一个 2.7 亿的模型可能会产生虚假的参数值。如果没有约束,请求“把它变成红色”可能会生成 {“color”: “crimson”} 或 {“color”: “rouge”}。枚举类型强制模型仅从有效值中选择,从而确保函数调用的可靠性。,推荐阅读爱思助手下载最新版本获取更多信息

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