Peak-Detector uses instruction-tuned LLMs and a condensed peak-representation of time-series data to achieve robust cross-modal peak detection with self-generated explanations across ECG, PPG, BCG, and BSG signals.
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2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Only 0.4% of 1,000 Android apps show consistent alignment between their privacy policies and actual log contents, while 67.6% leak sensitive information not mentioned in policies.
citing papers explorer
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Peak-Detector: Explainable Peak Detection via Instruction-Tuned Large Language Models in Physiological Sign
Peak-Detector uses instruction-tuned LLMs and a condensed peak-representation of time-series data to achieve robust cross-modal peak detection with self-generated explanations across ECG, PPG, BCG, and BSG signals.
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Do Privacy Policies Match with the Logs? An Empirical Study of Privacy Disclosure in Android Application Logs
Only 0.4% of 1,000 Android apps show consistent alignment between their privacy policies and actual log contents, while 67.6% leak sensitive information not mentioned in policies.