Difference between revisions of "NLP Status Report 2016-12-05"

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|Shiyue Zhang ||  
 
|Shiyue Zhang ||  
* found a bug in my code and modified it.
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* draw tsne pictures  [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/2f/RNNG%2Bmm%E5%AE%9E%E9%AA%8C%E6%8A%A5%E5%91%8A.pdf report]]
* tried memory with gate and found a big problem of memory.
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* try a trained gate to switch between rnng and mem, which got a slightly better result.  
* reran previous models, the results are not better than baseline. [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/2f/RNNG%2Bmm%E5%AE%9E%E9%AA%8C%E6%8A%A5%E5%91%8A.pdf report]]
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* reran the original model setting same seed, and got exactly same result.
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* published a TRP [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/Publication-trp]
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* try to solve the problem of mem
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|Guli ||
 
|Guli ||

Revision as of 06:06, 5 December 2016

Date People Last Week This Week
2016/12/05 Yang Feng
  • rnng+MN: got the result of k-means method and the result is slightly worse;
  • fixed the bug;
  • analyzed the memory units and changed the calculation of similarity and reran.
  • S2S+MN: read the code and discuss with andy about the implementation details;
  • checked Wikianswers data and found the answers are usually much longer than the question;
  • read 12 QA-related papers in proceedings of ACL16 and EMNLP16 and haven't found proper dataset yet.
  • Huilan's work: got a version of better result focusing on syntactical transformation.
  • rnng+MN: get the result with new similarity calculation.
  • S2S+MN: revise the code of tensorflow to make it equivalent to theano's.
  • poetry: review the code of Jiyuan
  • Huilan's work: continue the work of adding syntactic information.
Jiyuan Zhang
  • restructured code
  • found the cause of cost randomness
  • modified memory weight,ran expriment 言情风格边塞风格无风格
  • read a paper[1]
  • simply explain my code to Miss Feng
  • discussed with liantian about the way of using tensorflow to realize his idea
  • improve poem model
Andi Zhang
  • turn to focus on tensorflow codes
  • finish code outputing encoder outputs but have some problems with format
  • finish the part mentioned left
Shiyue Zhang
  • draw tsne pictures [report]
  • try a trained gate to switch between rnng and mem, which got a slightly better result.
Guli
  • preparing more data set
  • working on add translate module to code
  • writing a survey about Chinese-uyghur MT
  • prepare more data
  • prepare for Thesis Report