Generative agents with memory streams, reflection, and planning using LLMs exhibit believable individual and emergent social behaviors in a simulated town.
A Generalization of Sampling Without Replacement from a Finite Universe
11 Pith papers cite this work. Polarity classification is still indexing.
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TS-Neyman uses posterior sampling of stratum variances to implement an adaptive Neyman allocation rule that converges almost surely to the oracle proportions and achieves near-oracle efficiency in finite-strata settings.
EVENT5Ws is a new large-scale, manually verified open-domain event extraction dataset that benchmarks LLMs and demonstrates cross-context generalization.
SCARFACE provides a harmonized annual panel dataset of over 2,700 socio-economic, environmental, and agricultural indicators for 256 sub-regions in the Po Valley, Italy, spanning 2011 to 2024.
Derives a closed-form task-specific strictly proper scoring rule for ATE estimation by matching local curvature of the IPW error metric.
OPAL learns optimal smooth labeling policies from ML uncertainty scores to enable low-variance prediction-assisted inference with finite-sample coverage guarantees.
Quantum kernel methods show no statistically significant edge over strong classical baselines on tabular classification tasks, with current feature maps failing to match the spectral properties of the best classical kernel.
Case study of 18,020 Kubernetes PRs shows label-diff congruence is prevalent and stable, with higher congruence linked to fewer review participants among core developers and more among one-time contributors.
Develops unified formulas for conditional quantities and transportation functionals via distributional derivatives and copulas, yielding quantile representations for Wasserstein distance and applications to normal approximation of counting distributions.
MODEE is a multimodal system that integrates graphs with LLM embeddings to outperform prior open-domain event extraction methods on large datasets.
Self-reported LLM usage frequency associates more consistently with pre-instruction AI perceptions than prior education or self-rated familiarity in graduate trainees.
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SCARFACE: a harmonized spatio-temporal dataset integrating socio-economic, environmental, and agricultural indicators for the Po Valley (Italy), 2011--2024
SCARFACE provides a harmonized annual panel dataset of over 2,700 socio-economic, environmental, and agricultural indicators for 256 sub-regions in the Po Valley, Italy, spanning 2011 to 2024.