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Validation Set: We have shared 3 CSV files containing human-annotated validation sets of our paper (Validation Data.zip). AST and Student Code Correction: For generating AST and code correction, please check the two files, AST.py and Top1.py ( in AST & Top-1.zip ). In AST.py, we present the output of different parts of the program with an example. Please read that one before Top1.py. We follow the implementation of https://github.com/Lsdefine/attention-is-all-you-need-keras. Please check the remaining code in the above link. We made a minor correction in the dataloader.py to use two separate vocabulary cutoffs for input and output. dataloader1.py, transformer1.py, etc. are an exact replication of dataloader.py and transformer.py. Since we are using two models, we did it that way to avoid any conflict. TypeFix: Check the code in TypeFix.zip. Note: We have not published the training and test dataset of different models here. We will publish the complete package upon acceptance of our paper.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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