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834 papers, from 4 September 2026 to 5 November 2026: 834 arXiv preprints.
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A Unifying Perspective on Probabilities as Model Predictions
Although probabilistic statements are ubiquitous, foundational disagreements persist about their understanding, as exemplified by debates between Bayesians and frequentists; moreover, it is unclear…With a Thermomix You Lose the Ability to Cook: A Kitchen Machine Analogy for Applications of Generative AI in Education
The rapid adoption of generative AI tools such as ChatGPT has sparked intense debate about their risks and opportunities for education, as well as the ways researchers should investigate them.When Does Defendant Statement Matter? A Study of Bias and Persuasion in LLM-Simulated Jurors
LLMs have been used to simulate human decision-making in professional settings, yet their behaviors in common-law jury trials remain unexplored.Strangers to Themselves: What Language Models Say About Themselves Is Generic
Language models can fluently describe how they would behave: whether they would cave to pushback, misuse a tool, or lie under pressure.Beyond Training: A Feasibility Taxonomy for Inference-Time AI Governance
Compute governance today is a governance of training: the thresholds, reporting requirements, and frontier-AI regimes now in force attach to training compute and treat the trained model as the…Cyber-Financial Contagion: Modeling the Propagation of an AI Vendor Compromise Through the Banking System
The banking system now depends on a small set of shared artificial intelligence vendors for fraud screening, credit decisioning, anti-money-laundering triage, customer analytics, and internal…Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization
The growing complexity of content moderation policies presents a critical challenge for their consistent operationalization.Emergency Department Revisit Quality Review Screening: Exploring Human Decision-Making and Artificial Intelligence Support
Emergency Department (ED) return visits are commonly reviewed for quality assurance, but are often limited (e.g., to revisits within 48-72 hours) to increase actionable finding yield while…Following the Preference, Missing the Optimum: Compliance Without Optimization in AI Housing Recommendation
Large language models are becoming the first point of contact for consumer search in domains where the stakes are material and the law is explicit.Navigating the digital spectrum: Assessing political bias, stability, and downstream fairness in Large Language Models
Large Language Models are increasingly deployed as information intermediaries, yet measuring their political behavior remains fragile because questionnaire results mix model dispositions with…Silent Revision: Measuring Undisclosed Change in the Safety Frameworks of Frontier AI Developers
Frontier AI developers publish safety frameworks that commit them to evidencing whether their models are dangerous.The Audit Decides the Verdict: Instrument Effects Rival Demographic Bias in LLM Decision Audits
Whether a language model looks demographically biased can depend on how the audit asks its question.Auditable Emergency Triage for Maternal and Newborn Care in India
At Noora Health, our nurses answer more than 50,000 medical queries per month on our WhatsApp-based service that provides caregivers with on-demand support.Applying foundation model embeddings towards urban livability evaluation
While accurate measurement of socioeconomic indicators remains challenging in data-scarce regions, which limits policy interventions and resource allocation, high-resolution geospatial data is…The Mutations of Machine Speech
Algorithmic outputs now populate the digital environments through which contemporary life is organized.EmoMed: An Emotionally-Aware Agent for Multimodal Medical Support with Real-Time Information Retrieval
We present EmoMed - a multimodal medical consultation agent that adapts its responses based on users' emotional states while maintaining clinical accuracy.Human-like moral judgments conceal divergent motive attributions in large language models
Large language models (LLMs) are used to simulate human participants in psychological research.Mapping the Emerging Social Science of Large Language Models
Large language models (LLMs) increasingly shape communication, learning, work, creativity, and decision-making, yet social-science research on these developments remains fragmented.Norms at a Price: Why RL-Based Alignment Can Promise Conditional Compliance at Best
AI agents sometimes act aligned when they infer they are being tested, and differently when not.An emancipatory vision for designing (generative) AI for learner flourishing
The hype around generative AI seems to promise unprecedented productivity (and learning) gains.