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Peng Li

4 papers hereh-index 9339 citations15 works total

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

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • cs.LG1
same name
  • Peng Li — 16 papers, h 65
  • Peng Li — 12 papers
  • Peng Li — 9 papers, h 12
  • Peng Li — 9 papers, h 13
  • Peng Li — 8 papers, h 14
  • Peng Li — 7 papers, h 6

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

most citedLearning to Recover from Multi-Modality Errors for Non-Autoregressive Neural Machine Translation

2 citations · 5 across the 3 of their papers we have counts for

collaborators

4 papers

cs.LG2020★ 2 cited

Disentangle-based Continual Graph Representation Learning

Xiaoyu Kou, Yankai Lin, Shaobo Liu +3

Graph embedding (GE) methods embed nodes (and/or edges) in graph into a low-dimensional semantic space, and have shown its effectiveness in modeling multi-relational data. However,…

cs.CL2020★ 1 cited

DisenE: Disentangling Knowledge Graph Embeddings

Xiaoyu Kou, Yankai Lin, Yuntao Li +4

Knowledge graph embedding (KGE), aiming to embed entities and relations into low-dimensional vectors, has attracted wide attention recently. However, the existing research is mainl…

cs.CL2020

WeChat Neural Machine Translation Systems for WMT20

Fandong Meng, Jianhao Yan, Yijin Liu +8

We participate in the WMT 2020 shared news translation task on Chinese to English. Our system is based on the Transformer (Vaswani et al., 2017a) with effective variants and the DT…

cs.CL2020★ 2 cited

Learning to Recover from Multi-Modality Errors for Non-Autoregressive Neural Machine Translation

Qiu Ran, Yankai Lin, Peng Li +1

Non-autoregressive neural machine translation (NAT) predicts the entire target sequence simultaneously and significantly accelerates inference process. However, NAT discards the de…

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