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QA-GNN (https://github.com/michiyasunaga/qagnn from a Stanford lab) had some issues with their evaluation, but more importantly this work 'GNN is counting?...' (https://openreview.net/forum?id=hzmQ4wOnSb) showed that they can achieve better results with an extremely simplistic 1-dim GNN model - so the performance of QA-GNN was mainly due to data. AFAIK there were discussions around this, but now if you go to QA-GNN repo they have disabled issues tab.
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