Update description2code

_requests_for_research/description2code

@@ -17,7 +17,7 @@ difficulty: 3 # out of 3
 <p> To get started, proceed according to the following stages: </p>
 
   <ul>
-    <li> Download a large number of short description-code pairs from (dataset in-progress) for the purpose of training/testing. Try to use pairs that have the code written in the same language for all the pairs (the language should be one that is adopted by a substantial portion of the community). It would be convenient if someone (such as maybe <a href="https://triplebyte.com/">Triplebyte</a>) also created an easily downloadable dataset of description-code pairs arranged in order of increasing complexity so that a curriculum learning schedule could be used. </li>
+    <li> Download a large number of short description-code pairs from (dataset in progress) for the purpose of training/testing. Try to use pairs that have the code written in the same language for all the pairs (the language should be one that is adopted by a substantial portion of the community). It would be convenient if someone (such as maybe <a href="https://triplebyte.com/">Triplebyte</a>) also created an easily downloadable dataset of description-code pairs arranged in order of increasing complexity so that a curriculum learning schedule could be used. </li>
     <li> Might need need a reasoning component such as <a href="https://arxiv.org/pdf/1603.01417.pdf">(Dynamic?) Memory Networks </a> (or <a href="http://arxiv.org/pdf/1606.02270.pdf">EpiReader </a> in the case of scaling to longer description) to reason about meaning of and iteratively attend to memories of text/images within the description. A <a href='https://github.com/ethancaballero/Improved-Dynamic-Memory-Networks-DMN-plus'>Theano implementation</a> of the <a href="https://arxiv.org/pdf/1603.01417.pdf">Dynamic Memory Networks for textual and visual qa</a> paper can help you get started. </li>
     <li> Might need an interface-interaction component such as <a href="http://arxiv.org/pdf/1505.00521.pdf">Reinforcement Learning Neural Turing Machines</a> to interact with external interface such as google's search engine in order to look up relevant concepts that are referenced but not explained in the description. </li>
     <li> Might need a compositional component such as <a href="https://arxiv.org/pdf/1511.06279.pdf">Neural Programmer-Interpreter</a> or <a href="http://arxiv.org/pdf/1511.04834.pdf">Neural Programmer</a> to learn to compose higher-level programs from simpler sub-programs/operations. </li>