Two recent arXiv papers explore the application of generative AI models in decision-making scenarios. The first paper, "Generative models for decision-making under distributional shift," focuses on using flow- and score-based generative models to construct decision-relevant distributions for robustness and uncertainty quantification. The second paper, "Generative AI for Managerial Decision-Making under Ambiguity and Sycophancy," investigates how generative AI performs in business contexts, assessing its ability to handle ambiguity and its susceptibility to sycophantic behavior when given flawed directives. AI
IMPACT These papers explore novel applications of generative AI in complex decision-making scenarios, potentially improving robustness and strategic planning in business and operations research.
RANK_REASON Two academic papers published on arXiv discussing applications of generative AI.
- Fabrizio Marozzo
- Generative AI
- Managerial decision-making
- alphaXiv
- arXiv
- CatalyzeX Code Finder for Papers
- DagsHub
- Gotit.pub
- Hugging Face
- ScienceCast
- Yao Xie
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