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OSGuard addresses a critical blind spot in evaluating computer-use agents — while many benchmarks assess whether agents complete tasks as instructed, they often ignore safety failures where unsafe s…
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This paper addresses the complex problem of dynamic route optimization and disruption-aware scheduling in heterogeneous multi-gauge railway systems
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This paper addresses the challenge of extracting high-level, interpretable user activities from noisy, granular, and domain-specific low-level action sequences logged by digital applications
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This paper addresses the challenge of correcting burst synchronization errors—specifically bursts of consecutive insertions or deletions—in labeling sequences used in DNA-based data storage
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This paper develops a bond-operator theory (BOT) as an analytical framework to study the t–J model and its extensions, which is a central model for strongly correlated electrons especially relevant…
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This paper addresses the challenge of discovering interpretable, nonlinear constitutive material models directly from full-field displacement and reaction force data without requiring local stress …
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This paper addresses a critical challenge in deploying large language models (LLMs) to control real-world scientific experiments, specifically high-throughput experimentation (HTE)
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This paper tackles the challenging problem of feature importance interpretation in clustering, a widely used unsupervised learning tool for exploratory data analysis and scientific discovery
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This paper addresses the problem of accurately classifying cotton leaf diseases using deep learning, a critical task for improving cotton crop health and supporting agricultural economies
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This paper investigates the overlooked impact of bot detection and blocking on large-scale web measurement research that relies heavily on automated browser frameworks
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This work addresses the growing challenge of detecting highly realistic synthetic (spoofed) speech, a critical problem given advances in text-to-speech and voice conversion technologies
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This paper addresses the critical astrophysical problem of understanding the sources and evolution of cosmic reionization, focusing on predicting the escape fraction (f_esc) and escape rate (\dot{N…
