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Compressing Deep Neural Networks with Goal-Specific Pruning and Self-Distillation

Overview of attention for article published in ACM Transactions on Knowledge Discovery from Data, May 2025
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

patent
1 patent

Readers on

mendeley
12 Mendeley
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Article details
Title
Compressing Deep Neural Networks with Goal-Specific Pruning and Self-Distillation
Published in
ACM Transactions on Knowledge Discovery from Data, May 2025
DOI 10.1145/3721293
Authors

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Timeline Attention over time Attention Score history
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Activity
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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Lecturer 2 17%
Researcher 1 8%
Student > Ph. D. Student 1 8%
Unknown 8 67%
Readers by discipline
Readers by discipline Count As %
Engineering 2 17%
Pharmacology, Toxicology and Pharmaceutical Science 1 8%
Computer Science 1 8%
Physics and Astronomy 1 8%
Energy 1 8%
Other 0 0%
Unknown 6 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 March 2020.
All research outputs
#10,947,373
of 31,525,461 outputs
Outputs from ACM Transactions on Knowledge Discovery from Data
#85
of 363 outputs
Outputs of similar age
#103,470
of 322,549 outputs
Outputs of similar age from ACM Transactions on Knowledge Discovery from Data
#2
of 7 outputs
Altmetric has tracked 31,525,461 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 363 research outputs from this source. They receive a mean Attention Score of 3.5. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 322,549 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.