Just read another one of a myriad of #DeepLearning papers and realized that the authors are reporting trivia, but covering it up with an obscene amount of deep learning fluff and burned GPU time... I shall tear it apart in my next blog post. Stay tuned.
— Filip Piekniewski (@filippie509) July 13, 2018
OK, as promised here is a small autopsy of a paper I recently came across: https://t.co/uv7Vm0W4YX #Deeplearning #AI https://t.co/6d0GafR84q
— Filip Piekniewski (@filippie509) July 15, 2018
So true, unfortunately. In NLP, people have been adding position features to embeddings for a long time. I don’t think anyone has managed to write a whole paper about a one-line feature to make it sound academic. https://t.co/cb9AsRZWMO
— Denny Britz (@dennybritz) July 16, 2018
I really enjoyed the paper presentation, but the TLDR basically is: If your task cares about absolute positions it makes sense to add a position feature to your input! Do we need a paper for this?
— Denny Britz (@dennybritz) July 16, 2018
