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Fei Wu

53 papers hereh-index 5914.4k citations278 works total

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

author position
  • middle author37
  • last author14

Across the 51 of 53 papers where every author was matched, so the position is known.

fields
  • cs.CV29
  • cs.CL11
  • cs.LG5
  • cs.SI2
  • eess.IV2
  • cs.AI1
same name
  • Fei Wu — 52 papers, h 26
  • Fei Wu — 32 papers, h 23
  • Fei Wu — 15 papers, h 15
  • Fei Wu — 15 papers, h 5
  • Fei Wu — 13 papers, h 6
  • Fei Wu — 12 papers, h 7

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
20092022
most citedDeepSaliency: Multi-Task Deep Neural Network Model for Salient Object Detection

571 citations · 1.9k across the 53 of their papers we have counts for

collaborators
Showing 2019 · cs.CLShow all

4 papers · 2 filters

cs.CL2019★ 21 cited

Coreference Resolution as Query-based Span Prediction

Wei Wu, Fei Wang, Arianna Yuan +2

In this paper, we present an accurate and extensible approach for the coreference resolution task. We formulate the problem as a span prediction task, like in machine reading compr…

cs.CL2019★ 51 cited

A Unified MRC Framework for Named Entity Recognition

Xiaoya Li, Jingrong Feng, Yuxian Meng +4

The task of named entity recognition (NER) is normally divided into nested NER and flat NER depending on whether named entities are nested or not. Models are usually separately dev…

cs.CL2019★ 1 cited

Learning Dynamic Context Augmentation for Global Entity Linking

Xiyuan Yang, Xiaotao Gu, Sheng Lin +6

Despite of the recent success of collective entity linking (EL) methods, these "global" inference methods may yield sub-optimal results when the "all-mention coherence" assumption…

cs.CL2019

Posterior-regularized REINFORCE for Instance Selection in Distant Supervision

Qi Zhang, Siliang Tang, Xiang Ren +3

This paper provides a new way to improve the efficiency of the REINFORCE training process. We apply it to the task of instance selection in distant supervision. Modeling the instan…

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