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researcher

Yu Li

6 papers hereh-index 9230 citations18 works total

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

author position
  • first author3
  • middle author3

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CR1
  • cs.CV1
same name
  • Yu Li — 18 papers, h 10
  • Yu Li — 18 papers, h 7
  • Yu Li — 16 papers, h 8
  • Yu Li — 14 papers, h 5
  • Yu Li — 12 papers, h 9
  • Yu Li — 9 papers, h 16

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
20182024
most citedWhat You See is Not What the Network Infers: Detecting Adversarial Examples Based on Semantic Contradiction

19 citations · 35 across the 3 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2024★ 1 cited

Vector Quantization Prompting for Continual Learning

Li Jiao, Qiuxia Lai, Yu Li +1

Continual learning requires to overcome catastrophic forgetting when training a single model on a sequence of tasks. Recent top-performing approaches are prompt-based methods that…

cs.LG2021★ 13 cited

TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks

Yu Li, Min Li, Qiuxia Lai +2

Deep learning (DL) has achieved unprecedented success in a variety of tasks. However, DL systems are notoriously difficult to test and debug due to the lack of explainability of DL…

cs.LG2020

DeepDyve: Dynamic Verification for Deep Neural Networks

Yu Li, Min Li, Bo Luo +2

Deep neural networks (DNNs) have become one of the enabling technologies in many safety-critical applications, e.g., autonomous driving and medical image analysis. DNN systems, how…

cs.LG2018

On Configurable Defense against Adversarial Example Attacks

Bo Luo, Min Li, Yu Li +1

Machine learning systems based on deep neural networks (DNNs) have gained mainstream adoption in many applications. Recently, however, DNNs are shown to be vulnerable to adversaria…

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