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Yang Feng

Institute of Computing Technology, Chinese Academy of Sciences

35 papers hereh-index 231.7k citations55 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author26
  • last author6

Across the 34 of 35 papers where every author was matched, so the position is known.

fields
  • cs.CL34
  • nucl-th1
affiliations
  • Institute of Computing Technology, Chinese Academy of Sciences
same name
  • Yang Feng — 40 papers, h 29
  • Yang Feng — 38 papers, h 14
  • Yang Feng — 16 papers, h 14
  • Yang Feng — 15 papers, h 11
  • Yang Feng — 13 papers, h 10
  • Yang Feng — 12 papers, h 8

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172023
most citedMinimizing the Bag-of-Ngrams Difference for Non-Autoregressive Neural Machine Translation

41 citations · 151 across the 22 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.CL2018

Improving the Robustness of Speech Translation

Xiang Li, Haiyang Xue, Wei Chen +3

Although neural machine translation (NMT) has achieved impressive progress recently, it is usually trained on the clean parallel data set and hence cannot work well when the input…

cs.CL2018

Greedy Search with Probabilistic N-gram Matching for Neural Machine Translation

Chenze Shao, Yang Feng, Xilin Chen

Neural machine translation (NMT) models are usually trained with the word-level loss using the teacher forcing algorithm, which not only evaluates the translation improperly but al…

cs.CL2018

Speeding Up Neural Machine Translation Decoding by Cube Pruning

Wen Zhang, Liang Huang, Yang Feng +2

Although neural machine translation has achieved promising results, it suffers from slow translation speed. The direct consequence is that a trade-off has to be made between transl…

cs.CL2018

Refining Source Representations with Relation Networks for Neural Machine Translation

Wen Zhang, Jiawei Hu, Yang Feng +1

Although neural machine translation with the encoder-decoder framework has achieved great success recently, it still suffers drawbacks of forgetting distant information, which is a…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.