Classification with Binary Neural Network

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

8 shown of 8 papers with code (13 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
  16 Mar 2016 20 repositories listed Syntology ran 7 of 18 samples · 11 unverified · 3 pointer-only (licence)
  We propose two efficient approximations to standard convolutional neural networks: Binary-Weight-Networks and XNOR-Networks.
• AdaBin: Improving Binary Neural Networks with Adaptive Binary Sets
  17 Aug 2022 3 repositories listed Syntology ran 2 of 5 samples · 3 unverified · 3 pointer-only (licence)
  Since the modern deep neural networks are of sophisticated design with complex architecture for the accuracy reason, the diversity on distributions of weights and activations is very high.
• BiPer: Binary Neural Networks using a Periodic Function
  1 Apr 2024 1 repository listed
  In contrast to current BNN approaches, we propose to employ a binary periodic (BiPer) function during binarization.
• Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network
  17 Mar 2021 1 repository listed
  In this paper, we propose (and prove) a stronger Multi-Prize Lottery Ticket Hypothesis: A sufficiently over-parameterized neural network with random weights contains several subnetworks (winning tickets) that (a) have…
• High-Capacity Expert Binary Networks
  7 Oct 2020 1 repository listed Syntology ran 2 of 6 samples · 4 unverified
  Network binarization is a promising hardware-aware direction for creating efficient deep models.
• Training Binary Neural Networks with Real-to-Binary Convolutions
  25 Mar 2020 1 repository listed
  This paper shows how to train binary networks to within a few percent points (∼3-5 %) of the full precision counterpart.
• XNOR-Net++: Improved Binary Neural Networks
  30 Sep 2019 1 repository listed
  This paper proposes an improved training algorithm for binary neural networks in which both weights and activations are binary numbers.
• Improved training of binary networks for human pose estimation and image recognition
  11 Apr 2019 1 repository listed
  Big neural networks trained on large datasets have advanced the state-of-the-art for a large variety of challenging problems, improving performance by a large margin.

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.