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Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness

Paper recorded by Signals 4 on 2026-09-04 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07

Category: cs.AI · 人工智能 · first seen 2026-09-07

Abstract

Building automation systems generate rich sensor data yet remain insight-poor because heterogeneous point naming, missing metadata, and fragmented documentation obstruct their operational use. This systematic review analyses and codes 66 peer-reviewed studies on large language models (LLMs) for HVAC operations published between 2023 and March 2026. Each study is classified across five application

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#179 most recent of 300 cs.AI papers we have recorded · ↑ newer: RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Task · ↓ older: How Does mHC Use Its Residual Streams? Selective Routing and Near-Iden
Cite this page: Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness: the #179 most recent of 300 cs.AI papers we have recorded (as of 2026-09-04). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/large-language-models-for-hvac-operations-in-building-energy-systems-a-critical-.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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