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834 papers, from 4 September 2026 to 5 November 2026: 834 arXiv preprints.
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Newest papers, page 17
Social Bias or Social Desirability? Comparing Factorial Survey Experiments for Humans and Large Language Models
Factorial survey experiments are a survey method from the social sciences that uses descriptions of socially complex situation (``vignettes'') to elicit judgments such as social bias.Towards Green AI: Evaluating Energy Efficiency for Quantized LLM Inference
While it is known that quantization of large language models (LLMs) reduces memory usage via lower-bit weights, studies quantifying the resulting impact on energy usage and carbon intensity are…A null model to detect coordinated online behavior integrating evidence from multiple indicators
Coordinated online accounts can amplify messages and manipulate attention, but detecting such behavior is challenging due to confounding factors like account activity and item popularity.Technology-Supported Moderation in Online Deliberation
Mini-publics are an increasingly popular family of democratic innovation to broaden citizen engagement.How Reliable Are Large Language Models for Soil Organic Carbon Assessment? An Australian Benchmark
Soil organic carbon (SOC) is an indicator of agricultural soil condition and carbon storage, but numerical outputs from large language models (LLMs) require validation before use in monitoring or…Institutionalizing Trust in Data Exchange: Trust-Anchor Model of the Data Credit Guarantee Organization and Its Simulation-Based Comparison
Data trading markets that span industries and regions are expanding, but the implicit trust that supports data use within an organization does not carry over to cross-domain exchange.The Singularity Has a Distribution: Exact Timing Laws and Detection Limits for a Stochastic Intelligence Explosion
Automating AI research creates a positive feedback loop between software capability and research effort.How Safe Is ChatGPT Health Advice? Evidence from Real User Conversations in Four Global South Countries
People increasingly bring their health questions to ChatGPT, yet safety evaluations of LLM health advice rest almost entirely on clinician-authored vignettes, synthetic prompts, or simulated user…A Global View of How LLMs Value Human Time
Large language models (LLMs) increasingly act as personal assistants; however, little is known about how they capture national-level preferences on a global scale.Decomposing and Predicting Annotation Disagreement in Harmful Content Across Languages
Annotator disagreement is increasingly recognized as a meaningful property of subjective tasks, rather than merely noise to be removed.Fairness under Prediction Error in Predict-then-Optimize Pipelines
Fairness constraints in predict-then-optimize pipelines are necessarily enforced on predicted outcomes $\hat{y}$, since true outcomes $y$ are unobserved at decision time.AgentStripes: An Evidence-Graded Maturity Model for AI Agents
Benchmarks report what an Artificial Intelligence (AI) agent can do on a task suite, but not whether one released version has been engineered with the controls that make it reliable, safe and…Looking Complete Is Not Being Grounded: Evaluating LLM Sitreps Against Human-Authored Situation Reports
Evaluation for automatic crisis reporting should measure what practitioners need, not what is convenient to compare.Trust Before Autonomy: Rethinking Agentic Remote Sensing for Crisis Response
Agentic remote sensing is evaluated on how many questions it can answer, whereas crisis response depends on whether its answers can be relied on and how much of the decision can safely be handed to…MemeTrace: A Multimodal LLM-Based Agent for Safety-Aware Meme Provenance Analysis
Online memes are often carriers of unsafe content such as disinformation and propaganda.Whose Data, Whose Benchmark? A User-Centric Framework for Auditing Evaluation Resources
Benchmarks shape how model capabilities are measured and interpreted, yet their scores can obscure whose conventions, contexts, and judgments define successful performance.From Efficiency to Sufficiency: The Cost-Aware Measurement Design Framework for Automated Essay Scoring
Compute cost in automated essay scoring (AES) is usually treated as a technical efficiency issue rather than a measurement design concern.AI Representations of Mental Health Stigma: Quantifying the Gap Between AI Estimations and Human Perceptions Across Gender Groups Using GPT-Based LLMs
The increasing use of artificial intelligence (AI) in mental health applications raises concerns about its potential to internalize and perpetuate societal biases.Beyond Single-Pathogen Forecasts: Predicting Shared Respiratory Hospital Burden from Influenza, COVID-19, and RSV
Co-circulating influenza, COVID-19, and respiratory syncytial virus (RSV) create a shared hospital-admission burden, because beds, staff, testing capacity, and respiratory support are allocated to…{Access|Use|Sustain|_}-ability: Exploration and Quantification of a Linguistic Structure and Its Use in HCI
Language plays a crucial role in research and technology design, throughout problem formulation, method descriptions, analysis of findings, and interpretation.