  There has a been a significant rise in the use of Community Question
Answering sites (CQAs) over the last decade owing primarily to their ability to
leverage the wisdom of the crowd. Duplicate questions have a crippling effect
on the quality of these sites. Tackling duplicate questions is therefore an
important step towards improving quality of CQAs. In this regard, we propose
two neural network based architectures for duplicate question detection on
Stack Overflow. We also propose explicitly modeling the code present in
questions to achieve results that surpass the state of the art.
