arXiv AI
Jul 7
Out-of-Distribution Generalization of Risk Aversion in Language Models
arXiv:2607. 02755v1 Announce Type: cross Abstract: Training AIs to be risk-averse in resources could offer a failsafe in the event that AIs turn out misaligned.
Decision-Making under Combinatorial Risk
arXiv:2606. 10092v1 Announce Type: new Abstract: Decision-making under risk is typically studied through single-shot lottery choices.
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arXiv AI
Jul 14
Reproducing human biases in route choice using large language models: Toward scalable behavioral modeling
arXiv:2607. 11632v1 Announce Type: new Abstract: Human choice behavior, including route choice, exhibits systematic behavioral biases that deviate from the assumptions of full rationality.
arXiv AI
Jun 9
Beyond Rational Illusion: Behaviorally Realistic Strategic Classification
arXiv:2605. 19674v2 Announce Type: replace Abstract: Strategic classification(SC) studies the interaction between decision models and agents who strategically manipulate their features for favorable outcomes.
arXiv Machine Learning
Aug 4
BRiG-AFA: Bellman Risk-to-Go Learning for Non-Myopic Active Feature Acquisition
arXiv:2608. 02305v1 Announce Type: new Abstract: Active feature acquisition (AFA) asks which unobserved feature to measure next for each test instance under a budget.
arXiv Machine Learning
Jun 26
Embedding Foundation Model Predictions in Discrete-Choice Models with Structural Guarantees
arXiv:2606. 26432v1 Announce Type: new Abstract: Tabular foundation models achieve strong accuracy on choice prediction tasks, but their predictions often violate the economic logic those tasks require: raising a price can increase predicted demand, implied willingness-to-pay estimates are frequently negative or implausible, and unavailable alternatives receive nonzero probability.
arXiv AI
Jul 14
Behavioural Signatures of Risk-Sensitive Decision-Making in Large Language Models
arXiv:2607. 10251v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly used in decision support, it is important to understand whether their choices under uncertainty exhibit stable and interpretable behavioural regularities.
Hugging Face Trending Papers
Jul 13
Reproducing human biases in route choice using large language models: Toward scalable behavioral modeling
Human choice behavior, including route choice, exhibits systematic behavioral biases that deviate from the assumptions of full rationality. Cumulative prospect theory (CPT) has been widely recognized as an effective framework for characterizing such behavioral patterns.
arXiv AI
6d ago
SportD: How do VLMs physically strategize?
arXiv:2607. 14616v3 Announce Type: replace Abstract: Vision-language models (VLMs) can describe a scene, but can they act well within one?
arXiv Machine Learning
Jul 15
Learning an Interpretable Risk Scoring System for Maximizing Decision Net Benefit
arXiv:2604. 04241v2 Announce Type: replace Abstract: Risk scoring systems are widely used in high-stakes domains to assist decision-making.
arXiv Machine Learning
Aug 4
Conformal bandits: bringing statistical validity and reward efficiency under weak arm separability
arXiv:2512. 09850v2 Announce Type: replace Abstract: We introduce Conformal Bandits, a novel framework integrating Conformal Prediction (CP) into bandit problems, a classic paradigm for sequential decision-making under uncertainty.
arXiv AI
Jul 28
Rethinking Prospect Theory for LLMs: Revealing the Instability of Decision-Making under Epistemic Uncertainty
arXiv:2508. 08992v4 Announce Type: replace Abstract: Real-world decision-making often involves uncertainty expressed in linguistic rather than numerical terms, and Prospect Theory (PT) provides a classic framework for modeling human behavior under such uncertainty.
arXiv AI
Jul 13
Risk-Aware General-Utility Markov Decision Processes
arXiv:2607. 09298v1 Announce Type: cross Abstract: We study general-utility Markov decision processes (GUMDPs) with risk-aware objectives.