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Zheng Lin

Institute of Information Engineering, Chinese Academy of Sciences

7 papers hereh-index 171.2k citations53 works total

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

author position
  • middle author7

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.CV3
affiliations
  • Institute of Information Engineering, Chinese Academy of Sciences
Homepage
same name
  • Zheng Lin — 23 papers, h 15
  • Zheng Lin — 18 papers, h 15
  • Zheng Lin — 17 papers, h 4
  • Zheng Lin — 16 papers, h 6
  • Zheng Lin — 16 papers, h 5
  • Zheng Lin — 11 papers, h 5

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
20202026
most citedLearning Class-Transductive Intent Representations for Zero-shot Intent Detection

2 citations · 4 across the 7 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2022

Neural Label Search for Zero-Shot Multi-Lingual Extractive Summarization

Ruipeng Jia, Xingxing Zhang, Yanan Cao +3

In zero-shot multilingual extractive text summarization, a model is typically trained on English summarization dataset and then applied on summarization datasets of other languages…

cs.CL2021

Marginal Utility Diminishes: Exploring the Minimum Knowledge for BERT Knowledge Distillation

Yuanxin Liu, Fandong Meng, Zheng Lin +2

Recently, knowledge distillation (KD) has shown great success in BERT compression. Instead of only learning from the teacher's soft label as in conventional KD, researchers find th…

cs.CL2021

ROSITA: Refined BERT cOmpreSsion with InTegrAted techniques

Yuanxin Liu, Zheng Lin, Fengcheng Yuan

Pre-trained language models of the BERT family have defined the state-of-the-arts in a wide range of NLP tasks. However, the performance of BERT-based models is mainly driven by th…

cs.CL2020★ 2 cited

Learning Class-Transductive Intent Representations for Zero-shot Intent Detection

Qingyi Si, Yuanxin Liu, Peng Fu +3

Zero-shot intent detection (ZSID) aims to deal with the continuously emerging intents without annotated training data. However, existing ZSID systems suffer from two limitations: 1…

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