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## 🎉 News
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- 📄 [2025/04/18] (update #4): The paper related to the EPlus-LLMv2 platform has been accepted for publication in _Automation in Construction_.
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[Paper here](https://doi.org/10.1016/j.autcon.2025.106223).
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- ⚡️ [2025/01/15] (update #3): We release EPlus-LLMv2, successfully addressing the challenge of auto-building energy modeling (ABEM) in complex scenarios. The new version of the platform supports a wide range of modeling scenarios encountered in real-world building applications, significantly enhancing its breadth and flexibility. Based on comprehensive datasets and a large-scale LLM, we integrate techniques such as LoRA, mixed precision training, and model quantification to reduce computational burden and achieve efficient fine-tuning (without compensating performance).
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## 🎉 News
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- ⚠️ [2025/05/15] (update #5): A bug has been fixed and the model has been updated. Many thanks to the user for the feedback! Appreciated!!
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- 📄 [2025/04/18] (update #4): The paper related to the EPlus-LLMv2 platform has been accepted for publication in _Automation in Construction_.
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[Paper here](https://doi.org/10.1016/j.autcon.2025.106223).
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- ⚡️ [2025/01/15] (update #3): We release EPlus-LLMv2, successfully addressing the challenge of auto-building energy modeling (ABEM) in complex scenarios. The new version of the platform supports a wide range of modeling scenarios encountered in real-world building applications, significantly enhancing its breadth and flexibility. Based on comprehensive datasets and a large-scale LLM, we integrate techniques such as LoRA, mixed precision training, and model quantification to reduce computational burden and achieve efficient fine-tuning (without compensating performance).
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