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Jiawei Sheng

Institute of Information Engineering, Chinese Academy of Sciences

36 papers hereh-index 151k citations66 works total

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

author position
  • first author3
  • middle author32

Across the 35 of 36 papers where every author was matched, so the position is known.

fields
  • cs.CL19
  • cs.IR10
  • cs.LG3
  • cs.CV2
  • cs.MM2
affiliations
  • Institute of Information Engineering, Chinese Academy of Sciences
same name
  • Jiawei Sheng — 1 paper, h 1
  • Jiawei Sheng — 1 paper, h 1

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 citedContrastive Cross-Domain Sequential Recommendation

110 citations · 239 across the 31 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.CL2021

Improving Distantly-Supervised Named Entity Recognition with Self-Collaborative Denoising Learning

Xinghua Zhang, Bowen Yu, Tingwen Liu +4

Distantly supervised named entity recognition (DS-NER) efficiently reduces labor costs but meanwhile intrinsically suffers from the label noise due to the strong assumption of dist…

cs.CL2021

Event Extraction by Associating Event Types and Argument Roles

Qian Li, Shu Guo, Jia Wu +5

Event extraction (EE), which acquires structural event knowledge from texts, can be divided into two sub-tasks: event type classification and element extraction (namely identifying…

cs.CL2021★ 3 cited

CasEE: A Joint Learning Framework with Cascade Decoding for Overlapping Event Extraction

Jiawei Sheng, Shu Guo, Bowen Yu +5

Event extraction (EE) is a crucial information extraction task that aims to extract event information in texts. Most existing methods assume that events appear in sentences without…

cs.CL2021

A Survey on Deep Learning Event Extraction: Approaches and Applications

Qian Li, Jianxin Li, Jiawei Sheng +8

Event extraction (EE) is a crucial research task for promptly apprehending event information from massive textual data. With the rapid development of deep learning, EE based on dee…

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