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Towards Understanding of Medical Randomized Controlled Trials by Conclusion Generation

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Figure

Table 1: An example of the GPT-2 n = 0 model generating a false negative conclusion (Varenicline did reducegeneral craving), while the GPT-2 n = 1 model generated a better true negative one
Figure 3: The attention mask used during fine-tuning.White cells denote −∞ elements and grey cells denote0 in the mask matrix.
Table 3: Human evaluation results for text understand-ing on the annotation questions of 50 randomly selectedsource documents

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