1. although the choice of models seems fine at first, but I am not sure as to how much of the citation information is actually being utilized. The maximum input size can only be 1024 and given the size of articles and the abstracts I am not sure how much inforamtion is being used in either. Can you comment on how much information is lost at token-level that is being fed to model.
2. I like the idea of aggregation using various cited articles. The only problem and I might be possibly confused as to how are you ensuring the quality of chosen articles. It could be so that the claims made in the article might also be contradicting to the claims made in cited articles or might not at all be related to the claims being discussed in the articles. Do you have any analysis on correlation between cited articles and the main articles, and whether it affects the quality of generation?
3. The authors have reprt significane testing but I think the choice of test might be incorrect. Since the comparision is to be done between two samples generated from same input why not some paired test setting was used like wilcoxon signed ranked test?
3. The authors have reprt significane testing but I think the choice of test might be incorrect. Since the comparision is to be done between two samples generated from same input why not some paired test setting was used like wilcoxon signed ranked test?