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News/Layerwise Progressive Freezing: A Training Scaffold for Depth-Scalable Binary Networks
arxiv
PublishedJune 29, 2026 at 4:00 AM
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Layerwise Progressive Freezing: A Training Scaffold for Depth-Scalable Binary Networks

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2606.27759v1 Announce Type: new Abstract: Training binary neural networks (BNNs) from scratch is dominated by the straight-through estimator (STE), whose forward/backward mismatch produces severe accuracy degradation as networks deepen. We study an orthogonal axis: when and where binarization

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Discussion
Mentioned models
05
  • 01
    ResNet-50
  • 02
    ResNet-18
  • 03
    ResNet-34
  • 04
    MobileNetV2
  • 05
    BERT
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#binary-neural-networks#training-methods#deep-learning#optimization

No replies yet. Be first.

Mentioned models
05
  • 01
    ResNet-50
  • 02
    ResNet-18
  • 03
    ResNet-34
  • 04
    MobileNetV2
  • 05
    BERT
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#binary-neural-networks#training-methods#deep-learning#optimization

Related coverage

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