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Pre Training
%252C+which+pre-trains+on+biosignals+and+longitudinal+clinical+records+by+both+next-token+and+previous-token+prediction+in+alternating+transformer+layers.+This+pre-training+task+preserves+original+distribution+and+data+shapes+of+the+time-series.+Additionally%252C+the+full-rank+forward+and+backward+attention+matrices+exhibit+more+expressive+representation+capabilities.+Using+biosignals+and+longitudinal+clinical+records%252C+BiTimelyGPT+demonstrates+superior+performance+in+predicting+neurological+functionality%252C+disease+diagnosis%252C+and+physiological+signs.+By+visualizing+the+attention+heatmap%252C+we+observe+that+the+pre-trained+BiTimelyGPT+can+identify+discriminative+segments+from+biosignal+time-series+sequences%252C+even+more+so+after+fine-tuning+on+the+task.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.9df2e167e0b51305a98f20e840acb9b8%3frik%3drWuzvdFAws0KTg%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Autoregressive+Pre+Training&FORM=IRPRST&ck=B6846C7BBD172C1DE9D3B86411F5AA2C&selectedIndex=29&itb=0)
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