Enriched textual prompts lift local LLM accuracy on binary IoT environmental queries from 50.9-63.7% to 81.7-89.3% while preserving sub-second latency.
A general ai agent framework for smart buildings based on large language models and react strategy,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.PF 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing
Enriched textual prompts lift local LLM accuracy on binary IoT environmental queries from 50.9-63.7% to 81.7-89.3% while preserving sub-second latency.