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Mengnan Du

22 papers hereh-index 265.4k citations79 works total

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

author position
  • first author7
  • middle author12

Across the 19 of 22 papers where every author was matched, so the position is known.

fields
  • cs.LG10
  • cs.CV4
  • cs.CL2
  • cs.AI1
  • cs.CR1
  • cs.CY1
same name
  • Mengnan Du — 14 papers
  • Mengnan Du — 10 papers, h 18
  • Mengnan Du — 8 papers, h 3
  • Mengnan Du — 8 papers
  • Mengnan Du — 4 papers, h 3
  • Mengnan Du — 4 papers, h 3

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
20182022
most citedXFake: Explainable Fake News Detector with Visualizations

103 citations · 167 across the 10 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2020

Mitigating Gender Bias in Captioning Systems

Ruixiang Tang, Mengnan Du, Yuening Li +3

Image captioning has made substantial progress with huge supporting image collections sourced from the web. However, recent studies have pointed out that captioning datasets, such…

cs.CV2019

Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks

Haofan Wang, Zifan Wang, Mengnan Du +5

Recently, increasing attention has been drawn to the internal mechanisms of convolutional neural networks, and the reason why the network makes specific decisions. In this paper, w…

cs.CV2019

Towards Generalizable Deepfake Detection with Locality-aware AutoEncoder

Mengnan Du, Shiva Pentyala, Yuening Li +1

With advancements of deep learning techniques, it is now possible to generate super-realistic images and videos, i.e., deepfakes. These deepfakes could reach mass audience and resu…

cs.CV2018

Towards Explanation of DNN-based Prediction with Guided Feature Inversion

Mengnan Du, Ninghao Liu, Qingquan Song +1

While deep neural networks (DNN) have become an effective computational tool, the prediction results are often criticized by the lack of interpretability, which is essential in man…

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