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LLM as Clinical Graph Structure Refiner: Enhancing Representation Learning in EEG Seizure Diagnosis
This paper addresses the challenge of robust representation learning from noisy EEG data for automated seizure detection

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This paper addresses the challenge of robust representation learning from noisy EEG data for automated seizure detection

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This paper addresses the problem of accurate state estimation for nonlinear, agile unmanned aerial vehicles (UAVs) operating under degraded sensing conditions such as high sensor noise and sparse m…

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PuzzleMark addresses a very practical but underexplored problem: how to watermark high-value code datasets so an owner can later prove unauthorized use by neural code completion models, while avoid…

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RopeDreamer tackles long-horizon dynamics prediction for deformable linear objects (DLOs) such as ropes and cables, where standard learned predictors often drift, over-stretch links, or lose track …

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This paper addresses the challenging problem of statically attributing Android residential proxy malware APKs to specific commercial proxy networks

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DAMSA is a proposed very-short-baseline beam-dump experiment designed to search for short-lived particles that decay too early to be efficiently seen in conventional long-baseline beam-dump setups

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This paper asks a question that prior MEV work largely sidestepped: not how arbitrage is extracted, but which on-chain transaction(s) created the opportunity in the first place

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This paper addresses a critical gap in Table Question Answering (TQA) by focusing on implicit predictive reasoning tasks rather than explicit retrieval or aggregation of tabular facts

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This review paper surveys the systematic classification and phenomenological implications of Calabi-Yau (CY) threefolds in string cosmology, with a focus on global model building in type IIB string…

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This paper addresses the challenge of accurate lesion segmentation in medical images, which is complicated by the visual ambiguity of lesions that resemble surrounding tissues and have ill-defined …

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This paper addresses critical security and operational challenges in autonomous AI agent ecosystems, focusing on secure agent discovery, cryptographic authentication, capability attestation without…

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This paper asks a narrower question than the usual “does project-based learning work?” debate: in an introductory quantum mechanics course for engineers, does requiring students to finish their pro…