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Yang Liu

21 papers hereh-index 165.4k citations42 works total

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

author position
  • middle author5
  • last author16

Across the 21 of 21 papers where every author was matched, so the position is known.

fields
  • cs.CL19
  • cs.CV2
same name
  • Yang Liu — 129 papers, h 73
  • Yang Liu — 94 papers, h 65
  • Yang Liu — 41 papers, h 63
  • Yang Liu — 38 papers, h 23
  • Yang Liu — 35 papers, h 27
  • Yang Liu — 34 papers, h 39

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 citedTHUMT: An Open Source Toolkit for Neural Machine Translation

88 citations · 204 across the 21 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CL2022

An Extensible Plug-and-Play Method for Multi-Aspect Controllable Text Generation

Xuancheng Huang, Zijun Liu, Peng Li +3

Recently, multi-aspect controllable text generation that controls the generated text in multiple aspects (e.g., sentiment, topic, and keywords) has attracted increasing attention.…

cs.CL2022★ 1 cited

Continual Knowledge Distillation for Neural Machine Translation

Yuanchi Zhang, Peng Li, Maosong Sun +1

While many parallel corpora are not publicly accessible for data copyright, data privacy and competitive differentiation reasons, trained translation models are increasingly availa…

cs.CL2022

A Template-based Method for Constrained Neural Machine Translation

Shuo Wang, Peng Li, Zhixing Tan +3

Machine translation systems are expected to cope with various types of constraints in many practical scenarios. While neural machine translation (NMT) has achieved strong performan…

cs.CL2022★ 21 cited

Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

Ning Ding, Yujia Qin, Guang Yang +17

Despite the success, the process of fine-tuning large-scale PLMs brings prohibitive adaptation costs. In fact, fine-tuning all the parameters of a colossal model and retaining sepa…

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