Develops a reliable, efficient, and asymptotically optimal sequential multiple testing procedure that leverages prior information on hypothesis configurations across multiple data streams.
Levant, ``Exact differentiation of signals with unbounded higher derivatives,'' in Proc
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
LLM framework converts facial action unit sequences to text, fuses with responses, and regresses to personality scores, reporting lower errors and higher correlations than baselines on AVI-6.
citing papers explorer
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Sequential multiple testing with multiple hypotheses and prior information on the hypothesis configuration
Develops a reliable, efficient, and asymptotically optimal sequential multiple testing procedure that leverages prior information on hypothesis configurations across multiple data streams.
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LLM-based Multimodal Personality Recognition via Facial Action Unit-Text Semantic Fusion
LLM framework converts facial action unit sequences to text, fuses with responses, and regresses to personality scores, reporting lower errors and higher correlations than baselines on AVI-6.