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This paper addresses fairness-aware rank aggregation under the Spearman footrule distance metric, focusing on two key variants — (1) computing an optimal fair top-k aggregate ranking, and (2) approx…
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This study analyzes the human and community accuracy in detecting AI-generated media using a naturalistic dataset from r/RealOrAI, a dedicated Reddit community where users collaboratively judge vis…
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This paper addresses the challenge of systematically evaluating the rapidly growing and diverse open-source skill ecosystem designed to augment large language model (LLM) agents
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This paper investigates the efficacy of large-scale self-supervised pretraining, specifically DINOv3 distillation, compared to conventional supervised ImageNet pretraining for supervised industrial…
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This paper investigates the prevalence of AI-generated source content cited by prominent generative search engines (GSEs) such as ChatGPT, Copilot, Gemini, and Perplexity
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The VISTA benchmark addresses the gap in evaluating large language model (LLM)-based coding agents on realistic, end-to-end web application development tasks
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This work provides the first comprehensive, large-scale empirical analysis of authentication security in real-world remote Model Context Protocol (MCP) servers, a newly emerging infrastructure conn…
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This paper addresses a fundamental gap in evaluating Large Language Models (LLMs) — their ability to reproduce the relational structure of domain knowledge rather than just isolated facts
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This paper addresses the challenge of provisioning large spot instance fleets in cloud environments under uncertainty caused by dynamic pricing, availability, and interruptions that vary by region
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This paper addresses a key challenge in optical amplification — achieving high-gain, broadband, low-noise, and high-output-power amplification across an ultra-wide wavelength range beyond traditiona…
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This work addresses the challenge of automating detection of clinically important urological events—abdominal activity (ABD), detrusor overactivity (DO), and voiding contractions (VOID)—from single…
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This paper addresses the challenge of real-time cognitive load assessment using wearable ECG devices, which are limited by sparse lead configurations and small labeled datasets
