Large-scale review mining of 1M+ comments from 171 Gen-AI apps using an LLM framework reveals top topics plus three opportunities and three challenges for developers.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2025 2representative citing papers
Environment-conditioned parametric regression on 12-month indoor LoRaWAN data reduces cross-validated RMSE from 8.23 dB to 7.38 dB and lowers the fade margin needed for 99% reliability from ~28 dB to 25.73 dB.
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Understanding the Challenges and Opportunities of Generative AI Apps: An Empirical Study
Large-scale review mining of 1M+ comments from 171 Gen-AI apps using an LLM framework reveals top topics plus three opportunities and three challenges for developers.
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Environment-Aware Indoor LoRaWAN Path Loss: Parametric Regression Comparisons, Shadow Fading, and Calibrated Fade Margins
Environment-conditioned parametric regression on 12-month indoor LoRaWAN data reduces cross-validated RMSE from 8.23 dB to 7.38 dB and lowers the fade margin needed for 99% reliability from ~28 dB to 25.73 dB.