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Paper Citation Record · LEDGER

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs

As of 15 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:1908.07748.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.07748 v2

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:12:37.062181Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

21 of 21 outbound references displayed

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  • verified fuzzy12
  • unresolved8
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 28dd6e58-c423-410a-83bf-9b65ccee5a68 · outbound

This paper cites Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 88b1ef62-f4f0-4a09-8b72-c070bcec7485 · outbound

This paper cites Loss-aware Binarization of Deep Networks.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Loss-aware Binarization of Deep Networks

Reference 4

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verified exact
local_arxiv, observed 2026-08-14T12:12:37.147041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 726429ca-5b10-4c2b-b67c-cbafa03116a9 · outbound

This paper cites GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3ec405a5-d40c-42ff-bbb0-0ddd3ce77a2c · outbound

This paper cites Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:12:37.025729Z digest=sha256:171f1cbb664f1acb40e4a8774e0e9414dd70147eabe380a3ca6842d584e93810

Observation 3e3feb98-081a-43f9-a2ad-885b0234463b · outbound

This paper cites A benchmark and simulator for uav tracking.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs A benchmark and simulator for uav tracking

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ff5d2146-3633-412d-8c6b-a8e98ca2cdc9 · outbound

This paper cites Model compression via distillation and quantization.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Model compression via distillation and quantization

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:12:37.033048Z digest=sha256:2aa7f754e95ca24d215fc837d64a8179324d0b83f053bfd7db1ed9c6876095c6

Observation 09e1126f-031a-407d-bed8-3001107494eb · outbound

This paper cites Xnor-net: Ima- genet classification using binary convolutional neural net- works.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Xnor-net: Ima- genet classification using binary convolutional neural net- works

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 1f338a7c-f10a-4285-b8b3-7ff6694447d2 · outbound

This paper cites Imagenet large scale visual recogni- tion challenge.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Imagenet large scale visual recogni- tion challenge

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b96d09f5-1851-4442-b6b2-cfd2e2f4631b · outbound

This paper cites Online object tracking: A benchmark.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Online object tracking: A benchmark

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T12:12:37.046608Z digest=sha256:d929fd0f7b6c48101c299e0131551e9e2221d12425b4d851dfa8c35ee4607636

Observation 4e5118eb-1fb7-44b4-b637-8b3d131f39fe · outbound

This paper cites Wide Residual Networks.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Wide Residual Networks

Reference 18

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Unavailable: canonical work link unavailable.

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Observation 582d0bf4-f263-40c0-b01f-bd14e04128e2 · outbound

This paper cites Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ed1fabf7-29ac-4e02-b26f-17567e1a36b9 · outbound

This paper cites Trained Ternary Quantization.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Trained Ternary Quantization

Reference 20

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source=pdf_text observed=2026-08-14T12:12:37.058994Z digest=sha256:22df2c9d5911f4a89dfa0252fb359adf5150a2ea7a5a2ba46c447cbe9bfeb43a

Observation 356bed06-3071-4c79-add7-368d22c3ba79 · outbound

This paper cites Towards effective low-bitwidth convolutional neural networks.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Towards effective low-bitwidth convolutional neural networks

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d770855b-0232-4e55-9fb8-7708b3f460df · outbound

This paper cites Towards accurate binary convolutional neural network.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Towards accurate binary convolutional neural network

Reference 1998

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raw_fallback, observed 2026-08-14T12:12:37.249608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T12:12:37.019515Z digest=sha256:cfa71976af2b3775f42c570c18deb2ec5d51a920e6b053a3ba733171a9a10686

Observation 2525ad7c-a0ac-4984-9867-842972285bdf · outbound

This paper cites Gradient-based learning ap- plied to document recognition.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Gradient-based learning ap- plied to document recognition

Reference 2009

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ccf92ca6-455c-426f-869b-13b0640c9828 · outbound

This paper cites Object tracking benchmark.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Object tracking benchmark

Reference 2013

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verified fuzzy
raw_fallback, observed 2026-08-14T12:12:37.176480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T12:12:37.049508Z digest=sha256:247663afa583ba15c05e281e25bdb71e34cb75f5b30164451cdd5ee9afc23107

Observation 4f925c91-0f53-42ff-8ee0-10c1975400fc · outbound

This paper cites Modulated convolutional networks.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Modulated convolutional networks

Reference 2015

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T12:12:37.043609Z digest=sha256:a841ff9cff358c974513b04873b2b5b7d5f82ea3c062980a9be9087563a05369

Observation a0e6fdea-106b-47a5-812d-fa540aed4d94 · outbound

This paper cites Projection convolutional neural net- works.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Projection convolutional neural net- works

Reference 2016

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T12:12:36.997538Z digest=sha256:a17474a25083e0ee6e3fea4969045c10d1445bc3296d60a6de7d5d39a49ca48f

Observation 7edfb557-4f68-4ae0-affc-3083238f8ae2 · outbound

This paper cites Bi-real net: Enhancing the performance of 1-bit cnns with im- proved representational capability and advanced training algorithm.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Bi-real net: Enhancing the performance of 1-bit cnns with im- proved representational capability and advanced training algorithm

Reference 2017

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T12:12:37.022745Z digest=sha256:a5eb15078c2822dad51e1ecdf4b0526eff7f4260a273da80244a692be613ac9e

Observation 0e5ba297-052d-479f-88cc-7c3a4913f2d0 · outbound

This paper cites The cifar-10 dataset.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs The cifar-10 dataset

Reference 2018

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 05f387df-2627-4141-b358-6bb6e15b6d4a · outbound

This paper cites Deep residual learning for image recog- nition.

RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs Deep residual learning for image recog- nition

Reference 2019

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.