“NLP Status Report 2017-4-5”版本间的差异

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|Yang Feng ||
 
|Yang Feng ||
 
* Got the sampled 100w good data and ran Moses (BLEU: 30.6)
 
* Got the sampled 100w good data and ran Moses (BLEU: 30.6)
* Reimplemented the idea of ACL (added some optimization to the previous code) and check the performance in the following gradual steps: 1. use s\_i-1 as memory query; 2. use s\_i-1+c\_i
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* Reimplemented the idea of ACL (added some optimization to the previous code) and check the performance in the following gradual steps: 1. use s_i-1 as memory query; 2. use s_i-1+c_i as memory query; 3. use y as the memory states for attention; 4. use y + smt_attentions * h as memory states for attention.
as memory query; 3. use y as the memory states for attention; 4. use y + smt_attentions * h as memory states for attention.
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* ran experiments for the above steps but the loss was inf. I am looking for reasons.
 
* ran experiments for the above steps but the loss was inf. I am looking for reasons.
 
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2017年4月5日 (三) 02:16的最后版本

Date People Last Week This Week
2017/4/5 Yang Feng
  • Got the sampled 100w good data and ran Moses (BLEU: 30.6)
  • Reimplemented the idea of ACL (added some optimization to the previous code) and check the performance in the following gradual steps: 1. use s_i-1 as memory query; 2. use s_i-1+c_i as memory query; 3. use y as the memory states for attention; 4. use y + smt_attentions * h as memory states for attention.
  • ran experiments for the above steps but the loss was inf. I am looking for reasons.
  • do experiments and write the paper
Jiyuan Zhang
  • I did keyword expansion on the qx's model
  • fixed some bugs
  • read two papers
  • improve the effect of the qx's model
Andi Zhang
  • revise the original oov model so that it can automatically detect oov words and translate them
  • deal with the situation that source word is oov but target word is not oov first
  • it didn't predict right
  • make the model work as what we wanted
  • deal with the situation that source word is oov and target word is also oov, then other situations
Shiyue Zhang
  • got a reasonable baseline on big zhen data
  • implement mem model on this baseline, and test on big data
Peilun Xiao