In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
--------
Question: Three incremental levels of document preprocessing are experimented with: raw text, text cleaning through document logical structure detection, and removal of keyphrase sparse sections of the document. In doing so, we present the first consistent comparison of different keyphrase extraction models and study their robustness over noisy text.
Question: what levels of document preprocessing are looked at?

Answer: raw text text cleaning through document logical structure detection removal of keyphrase sparse sections of the document

Question: Furthermore, the basic seq2seq assumes a strict order between generated tokens, but in reality, we should not severely punish the model when it predicts the correct tokens in the wrong order.
Question: Do they impose any grammatical constraints over the generated output?

Answer: No

Question: At the moment defender can draw on methods from image area to text for improving the robustness of DNNs, e.g. adversarial training BIBREF107 , adding extra layer BIBREF113 , optimizing cross-entropy function BIBREF114 , BIBREF115 or weakening the transferability of adversarial examples.
Question: Which strategies show the most promise in deterring these attacks?

Answer:
At the moment defender can draw on methods from image area to text for improving the robustness of DNNs, e.g. adversarial training BIBREF107 , adding extra layer BIBREF113 , optimizing cross-entropy function BIBREF114 , BIBREF115 or weakening the transferability of adversarial examples.