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This paper addresses a critical open problem in adversarially robust streaming algorithms for frequency moments estimation in the insertion-deletion.
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This paper addresses the challenge of realizing continuous, narrow-linewidth superradiant emission from ensembles of quantum emitters for precision.
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This paper addresses a key weakness in current benchmarks for evaluating Large Language Models (LLMs) on data analysis tasks: their failure to capture.
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This study investigates the unique challenges and design needs of computerized gait analysis (CGA) specifically in pediatric care, an area underexplored.
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This study addresses the practical adoption landscape of Domain-Driven Design (DDD) by conducting the first large-scale empirical characterization of.
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EgoPolice is a novel benchmark dataset designed for egocentric video understanding in real-world police body-worn camera (BWC) footage.
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EvoCUA-1.5 addresses the challenge of training multi-turn computer-use agents that operate in partially observable, multimodal desktop environments.
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This paper addresses the problem of lightweight, interpretable, image-level forgery screening based on JPEG compression inconsistencies.
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This paper addresses the core challenge of modality interference in native end-to-end full-duplex Spoken Language Models (SLMs), which concurrently.
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This paper introduces the Hilti-Trimble-Oxford Dataset, a challenging visual-inertial benchmark designed for Simultaneous Localization and Mapping (SLAM).
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This paper addresses the challenge of autonomous robot planning in open-world household environments, where robots lack complete knowledge about objects.
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The paper addresses a critical gap in the automated testing of large language model (LLM) agent frameworks such as LangChain, LlamaIndex, and CrewAI.
