A DBM-based architecture learns consumer beliefs to enable consistent prediction and counterfactual inference for marketing interventions, outperforming baselines on heterogeneous treatment effects in simulation.
Language models are few-shot learn- ers.Advances in neural information processing sys- tems, 33:1877–1901
2 Pith papers cite this work. Polarity classification is still indexing.
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LLMs memorize citations hierarchically: titles and first authors are recalled at lower redundancy levels than venues or years, with accuracy scaling log-linearly and saturating near verbatim reproduction above roughly 1200 citations.
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Three-in-One World Model: Energy-Based Consistency, Prediction, and Counterfactual Inference for Marketing Intervention
A DBM-based architecture learns consumer beliefs to enable consistent prediction and counterfactual inference for marketing interventions, outperforming baselines on heterogeneous treatment effects in simulation.
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Hierarchical Memorization in Large Language Models: Evidence from Citation Generation
LLMs memorize citations hierarchically: titles and first authors are recalled at lower redundancy levels than venues or years, with accuracy scaling log-linearly and saturating near verbatim reproduction above roughly 1200 citations.