artificial intelligence

The Role of Using Artificial Intelligence Tools and Technologies in Detecting Forgery Crimes and Violations, Including Deep Fake Attacks " دور استخدام أدوات وتقنيات الذكاء الإصطناعي في إكتشاف جرائم وانتهاكات التزويير والتزييف العميق "

Potential to improve early detection of lung cancer through expansion of focused and opportunistic screening approaches: a scoping review focusing on potential expansion of screening risk factors and adoption of artificial intelligence models.

A scoping review was conducted to explore two potentially complementary approaches to enhance LC screening, including studies involving AI-augmented imaging (CXR or LDCT) to improve workflow, triage, and opportunistic nodule detection.

Artificial intelligence-based modeling of oxidative stress biomarkers: a comparison with the integrated biomarker response (IBR) approach

Measuring Concept Content in Text from LLM Activations: ESG Evidence from Concept Vectors and Linear Probes

Recent work shows that Large Language Models (LLMs) encode more information in their activations than they show in their responses. We ask whether the information contained in activations could be used as a source of measurement for the presence of concepts. We compare two algorithms for extraction of concepts, i.e., R...

Need or Reputation? Region, National Income, and Academic Status in LLM Gatekeeping Decisions

Equitable access to scientific knowledge often depends on informal gatekeeping decisions, particularly when resources such as paywalled articles, nonpublic datasets, or a researcher's CV must be shared selectively. We introduce a controlled simulation framework in which LLM-based professors must grant access to only on...

AI Alignment and Fiduciary Obligation

Advanced AI assistants engage users in extended interactions across a widening range of roles, including advice, decision support, collaboration, learning, emotional support, and companionship among others. Current alignment efforts consider what alignment criteria should govern these relationships, drawing on moral tr...

LLM-OSDA: An Optimal-Stopping Dynamic Auction for Native Advertising in Multi-Turn LLM Conversations

LLM-native advertising embeds sponsored content directly into model-generated responses, shifting the unit of sale from a fixed slot to a moment within an evolving conversation. Existing LLM ad-auction mechanisms primarily operate within a single response, settling the winner but not the timing. The extension is nontri...

COSI-Lab: Conference Living Lab for Modeling Multi-Perspective Multimodal Social Intention

A novel annotation process for AII is contributed that accounts for a perceiver's own interpretative tendencies and quantitative and qualitative analyses of intent narratives with respect to diversity, plausibility and grounding.

Activation Steering with Jungian Cognitive Functions

Controlling combinations of personality-related tendencies is important for adapting large language models to diverse interaction needs. But successful single-trait steering does not establish how to construct interventions for joint targets, or whether existing trait directions adequately represent them. We introduce...

Scaling Point-in-Time Language Models: Enabling Economic Evaluation of Embeddings

Large language models trained on unrestricted internet corpora inevitably embed information from the future, introducing lookahead bias that compromises the validity of backtests and causal inference in finance and the social sciences. Point-in-time language models--trained exclusively on text available up to each cale...

Comparing Socially-Equitable Renewable Energy Budget Allocation MDP Policies in Mature and Emerging Economies

Equitable renewable-energy planning is a sequential decision problem, but the decision variables available to a public planner differ sharply between mature and emerging economies. In the former the government largely builds generation, while in the latter it steers private investment through incentives and quotas. We...

An LLM-powered Agentic Recommendation System for Connected TV Content Discovery

Recommendation systems, from traditional multi-stage to recent unified generative architectures, face challenges in incorporating diverse contextual signals, such as trending topics, breaking news, cultural events, and cross-surface user activities, into their ranking pipelines. These systems are designed to consume st...