Helios: A Foundational Language Model for Smart Energy Knowledge Reasoning and Application (2026.eacl-long)
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| Challenge: | Enersys is a collaborative framework for end-to-end dataset construction that combines a large-scale pretraining, SFT, and RLHF datasets to improve performance. |
| Approach: | They propose a large language model tailored to the smart energy domain and a collaborative framework to advance LLM research in this field. |
| Outcome: | The proposed model improves domain knowledge mastery, task execution accuracy, and alignment with human preferences. |
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| Challenge: | Prior benchmarking efforts focused on latency reduction in idealized settings, often overlooking real-world inference workloads that shape energy use. |
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| Challenge: | Logic-based approaches to reasoning have lost popularity due to limited scalability and coverage. |
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