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CARE-Link is an open-source, web-based platform designed to improve gestational diabetes management by integrating electronic health records (EHR) with patient-generated data via WhatsApp, mediated…
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This study focuses on detailed cosmographic mapping of the Sloan Great Wall (SGW) and its associated large-scale structure through probabilistic reconstruction of cosmic density and velocity fields
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This paper investigates the effectiveness of Answer Engine Optimization (AEO)—a practice analogous to SEO that targets referrals from large language model (LLM) answer engines such as ChatGPT—on a …
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This paper investigates the reproducibility and domain-specificity of prompt-injection red-teaming results against state-of-the-art computer-using agents (CUAs)
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GraphAlg Playground is a fully client-side, web-based platform designed to teach and allow experimentation with GraphAlg, a domain-specific language for graph algorithms that integrates tightly wit…
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This paper presents a detailed content analysis of a rare, publicly released dataset from a controversial and ethically discontinued field experiment in which undisclosed LLM-powered synthetic acco…
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This paper addresses a key limitation in online skill learning for web automation agents — traditional approaches reuse skills only at the task level based on initial instructions and keep them fixe…
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This paper addresses the challenging problem of detecting AI-generated videos, which have become increasingly realistic and threaten misinformation and content trust
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This paper introduces SearchLog, a novel Chromium-based web browser extension designed for laboratory studies capturing naturalistic search logs during participants' open web search sessions
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SentinelBench addresses a pressing gap in AI agent evaluation — how to benchmark agents on long-running monitoring tasks that unfold over minutes to hours
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This paper presents SLUSCHI-UP, a publicly deployed web infrastructure for estimating melting temperatures of materials using the SLUSCHI small-size solid–liquid coexistence method combined with un…
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This paper investigates how well large language models (LLMs) can create synthetic individual-level digital twins using heterogeneous panel survey data rather than bespoke, purpose-collected datase…
