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AVSS:LayerImportanceEvaluationinLargeLanguageModelsviaactivationVariance-SparsityAnalysis
The evaluation of layer importance in deep learning has been an active area of research, with signif
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LocalLesionGenerationisEffectiveforCapsuleEndoscopyImageDataaugmentationinaLimitedDataSetting
Limited medical imaging datasets challenge deep learning models by increasing risks of overfitting a
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AlphaandPrejudice:Improving$α$-sizedWorst-caseFairnessviaIntrinsicReweighting
Worst-case fairness with off-the-shelf demographics achieves group parity by maximizing the model ut
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AStudyofDataaugmentationTechniquestoOvercomeDataScarcityinWoundClassificationusingDeepLearning
Chronic wounds are a significant burden on individuals and the healthcare system, affecting millions
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Select2Plan:Training-FreeICL-BasedPlanningthroughVQaandMemoryRetrieval
This study explores the potential of off-the-shelf Vision-Language Models (VLMs) for high-level robo
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EnhancingMaritimeSituationalAwarenessthroughEnd-to-EndOnboardRawDataanalysis
Satellite-based onboard data processing is crucial for time-sensitive applications requiring timely
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FUsion-basedConstitutivEmodel(FuCe):Towardsmodel-dataaugmentationinconstitutivemodelling
Constitutive modeling is crucial for engineering design and simulations to accurately describe mater
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SmokeScreensandScapegoats:TheRealityofGeneralDataProtectionRegulationCompliance--PrivacyandEthicsintheCaseofReplikaaI
Currently artificial intelligence (AI)-enabled chatbots are capturing the hearts and imaginations of
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ATutorialonTeachingDataanalyticswithGenerativeAI
This tutorial addresses the challenge of incorporating large language models (LLMs), such as ChatGPT
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OSCAR-PandaMLLibrary:ProfilingandPredictingthePerformanceofFaaS-basedApplicationsinComputingContinua
This paper proposes an automated framework for efficient application profiling and training of Machi
