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Jiajun Zhang

Institute of Automation Chinese Academy of Sciences

40 papers hereh-index 395k citations167 works total

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

author position
  • first author6
  • middle author30
  • last author3

Across the 39 of 40 papers where every author was matched, so the position is known.

fields
  • cs.CL37
  • cs.CV2
  • cs.LG1
affiliations
  • Institute of Automation Chinese Academy of Sciences
same name
  • Jiajun Zhang — 43 papers, h 14
  • Jiajun Zhang — 16 papers, h 13
  • Jiajun Zhang — 11 papers, h 5
  • Jiajun Zhang — 9 papers, h 6
  • Jiajun Zhang — 9 papers, h 4
  • Jiajun Zhang — 7 papers, h 4

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
20152023
most citedBridging Neural Machine Translation and Bilingual Dictionaries

46 citations · 300 across the 39 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.CL2018★ 1 cited

Language-Independent Representor for Neural Machine Translation

Long Zhou, Yuchen Liu, Jiajun Zhang +2

Current Neural Machine Translation (NMT) employs a language-specific encoder to represent the source sentence and adopts a language-specific decoder to generate target translation.…

cs.CL2018★ 5 cited

Source-Critical Reinforcement Learning for Transferring Spoken Language Understanding to a New Language

He Bai, Yu Zhou, Jiajun Zhang +3

To deploy a spoken language understanding (SLU) model to a new language, language transferring is desired to avoid the trouble of acquiring and labeling a new big SLU corpus. Trans…

cs.CL2018★ 2 cited

Phrase Table as Recommendation Memory for Neural Machine Translation

Yang Zhao, Yining Wang, Jiajun Zhang +1

Neural Machine Translation (NMT) has drawn much attention due to its promising translation performance recently. However, several studies indicate that NMT often generates fluent b…

cs.CL2018★ 6 cited

Learning Multimodal Word Representation via Dynamic Fusion Methods

Shaonan Wang, Jiajun Zhang, Chengqing Zong

Multimodal models have been proven to outperform text-based models on learning semantic word representations. Almost all previous multimodal models typically treat the representati…

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