StCP leverages transfer learning to stabilize the size of conformal prediction sets without additional target labels.
arXiv preprint arXiv:2505.13432 , year=
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LLM analysis of social media creates high-frequency CPI surrogates that, when jointly modeled in a deep panel framework, reduce short-term forecasting errors and better capture abrupt inflationary shifts than traditional econometric models.
A framework models proxy-primary outcome discrepancies as random effects at the parameter level, estimated from aggregated historical observations to calibrate inferences under distribution shifts.
citing papers explorer
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Stable Localized Conformal Prediction via Transduction
StCP leverages transfer learning to stabilize the size of conformal prediction sets without additional target labels.
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How Does LLM Help Regional CPI Forecast: An LLM-powered Deep Panel Modeling Framework
LLM analysis of social media creates high-frequency CPI surrogates that, when jointly modeled in a deep panel framework, reduce short-term forecasting errors and better capture abrupt inflationary shifts than traditional econometric models.
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Estimate Level Adjustment For Inference With Proxies Under Random Distribution Shifts
A framework models proxy-primary outcome discrepancies as random effects at the parameter level, estimated from aggregated historical observations to calibrate inferences under distribution shifts.