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Transformers Represent Belief State Geometry in their Residual Stream — LessWrong

Transformers Represent Belief State Geometry in their Residual Stream — LessWrong
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James crutchfieldGuillaume corlouerPaul riechersAlexander gietelink oldenzielSarah marzenLucas teixeiraIlya sutskeverLightspeed grantComputational mechanicsMixed state presentationHidden markov modelTransformers learnBelief stateGenerating processData generating processStochastic gradient descent

GitHub - continuousml/Awesome-Out-Of-Distribution-Detection: A professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc for Out-of-distribution detection, robustness, and generalization

A professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc for Out-of-distribution detection, robustness, and generalization - GitHub - continuousml/Awesome-Out-Of-Distribution-Detection: A professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc for Out-of-distribution detection, robustness, and generalization

Sri lankaDustin tranThomasg dietterichAlexander meinkeYibo zhouJie renVaishnavh nagarajanBalaji lakshminarayananNeeraj varshneySharon yixuan liJasper snoekExamples in neural networksPresence of limitedMitigating neural network overconfidenceConfidence for detection in neural networksEnergy regularization loss for detection