<p>Compiling a list of potential resources on it:</p>

<ol>
<li>"Word Embeddings and Their Use In Sentence Classification Tasks" by Amit Mandelbaum and Adi Shalev. <a href="https://arxiv.org/abs/1610.08229" rel="nofollow noreferrer">https://arxiv.org/abs/1610.08229</a></li>
</ol>
Word embedding as features for classification
<p>W.r.t text classification, now a common approach is to combine (often sum or average) word embeddings and use the result vector as features.</p>

<p>Are there any reference document(s) that establish the comparison of this approach for text classification over traditional feature engineering approaches? [Comparison based on accuracy] [could be on popular datasets like IMDB, sentiment-140 etc]</p>