Paper Citation Record · LEDGER

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions

As of 16 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:1908.03888.

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

pith.paper-citation-record.v1
1908.03888 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:03:09.319039Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

49 of 49 outbound references displayed

verified exact1
verified fuzzy24
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ac3e3aee-5231-4b64-bfee-bb003a501b00 · outbound

This paper cites Fast Patch-based Style Transfer of Arbitrary Style.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Fast Patch-based Style Transfer of Arbitrary Style

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.109791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb20c039-94c8-4a4c-81aa-dd6fb15ff732 · outbound

This paper cites Xception: Deep learning with depthwise separable convolutions.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Xception: Deep learning with depthwise separable convolutions

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.115521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfdf8c22-3384-4cc6-bc30-d0d0098e16e3 · outbound

This paper cites an unresolved cited work.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-14T14:03:09.967216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 06858dd8-43b5-422a-ac8d-bf2badc04277 · outbound

This paper cites Rich feature hierarchies for accurate object detection and semantic segmentation.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Rich feature hierarchies for accurate object detection and semantic segmentation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.125343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 544225c5-bdeb-4103-bfc5-0a71a7a35aaa · outbound

This paper cites Deep learning with limited numerical precision.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Deep learning with limited numerical precision

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.130196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7d2a190-f98d-4f48-978f-5482f0dfbaf8 · outbound

This paper cites Learn- ing both weights and connections for efﬁcient neural net- works.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Learn- ing both weights and connections for efﬁcient neural net- works

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.934109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 74fde9b2-7cb5-4491-831f-d3af81b0df70 · outbound

This paper cites Deep residual learning for image recognition.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Deep residual learning for image recognition

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.140070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edacb6e2-dcc6-4d3b-a4a3-805c757f55e3 · outbound

This paper cites Channel pruning for accelerating very deep neural networks.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Channel pruning for accelerating very deep neural networks

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.909724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 23612be2-0c08-4db2-8f4a-8c96796f7033 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.148903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 681e5213-218b-4d8b-a9b2-a559a9feb31b · outbound

This paper cites Squeeze-and-excitation net- works.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Squeeze-and-excitation net- works

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.153464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b0f0f83-10cb-481a-bc06-48207da5262a · outbound

This paper cites Condensenet: An efﬁcient densenet using learned group convolutions.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Condensenet: An efﬁcient densenet using learned group convolutions

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.885473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5e621eda-ee3f-41c9-bc98-e54ded6370d8 · outbound

This paper cites Densely connected convolutional net- works.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Densely connected convolutional net- works

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.161961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a47adbc9-5f1b-4e77-9167-0263b1be9a26 · outbound

This paper cites Speed/accuracy trade-offs for modern convolutional object detectors.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Speed/accuracy trade-offs for modern convolutional object detectors

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.862452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2f12d41b-4544-44cc-a4dd-775d4b07bbb8 · outbound

This paper cites Binarized neural networks.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Binarized neural networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.848406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 13784025-ac42-4b4e-b314-654b89cd09fd · outbound

This paper cites Squeezenet: Alexnet-level accuracy with 50x fewer parame- ters and <0.5mb model size.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Squeezenet: Alexnet-level accuracy with 50x fewer parame- ters and <0.5mb model size

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.834156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4aa9e8bc-e47b-4cdf-a536-128d7e45797b · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal co- variate shift.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Batch normalization: Accelerating deep network training by reducing internal co- variate shift

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.178819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fe34653-1214-4859-9399-e341dbfaa9de · outbound

This paper cites Flattened Convolutional Neural Networks for Feedforward Acceleration.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Flattened Convolutional Neural Networks for Feedforward Acceleration

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.183399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a27361de-b60f-4a65-88eb-5e26e928a925 · outbound

This paper cites Imagenet classiﬁcation with deep convolutional neural net- works.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Imagenet classiﬁcation with deep convolutional neural net- works

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.187815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 208ee8a9-dd5d-4378-a1e7-554174203d5a · outbound

This paper cites Pruning ﬁlters for efﬁcient convnets.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Pruning ﬁlters for efﬁcient convnets

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.798250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 588f8841-27a5-44f9-8326-f82123c51450 · outbound

This paper cites an unresolved cited work.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-14T14:03:09.783223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f312605a-ac2f-4a06-aa48-8ec7d34495b1 · outbound

This paper cites Fully convolutional networks for semantic segmentation.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Fully convolutional networks for semantic segmentation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.201569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36148977-419f-4e00-89cf-4204e28ed977 · outbound

This paper cites Shufﬂenet v2: Practical guidelines for efﬁcient cnn architec- ture design.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Shufﬂenet v2: Practical guidelines for efﬁcient cnn architec- ture design

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.759851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 344e3004-3913-46d0-83b1-f8f06ca9d81d · outbound

This paper cites Stacked hour- glass networks for human pose estimation.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Stacked hour- glass networks for human pose estimation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.744738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9448d49f-acf1-427b-a8a0-33fe943ff3d1 · outbound

This paper cites Automatic differentiation in pytorch.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Automatic differentiation in pytorch

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.214986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eebb9d2f-264e-4a93-a346-68e779f81c28 · outbound

This paper cites Accelerating Deep Neural Networks with Spatial Bottleneck Modules.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Accelerating Deep Neural Networks with Spatial Bottleneck Modules

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-14T14:03:09.361303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 49d40b4e-a528-41b5-b3fa-a72986c0cc98 · outbound

This paper cites Efﬁcient neural architecture search via parameter sharing.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Efﬁcient neural architecture search via parameter sharing

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.721013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 05eaf529-a6dc-4cb6-ad4e-93aa618113b4 · outbound

This paper cites an unresolved cited work.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-14T14:03:09.707111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 79d63b4a-affc-4e97-9f71-3cfb9afa7816 · outbound

This paper cites Unsuper- vised representation learning with deep convolutional gener- ative adversarial networks.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Unsuper- vised representation learning with deep convolutional gener- ative adversarial networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.693213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f1556cc5-d3fa-4e45-ad3e-aff6407f97de · outbound

This paper cites Xnor-net: Imagenet classiﬁcation using bi- nary convolutional neural networks.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Xnor-net: Imagenet classiﬁcation using bi- nary convolutional neural networks

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.677833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation df1d7594-4a59-4b07-8e27-b9c68fe9dbae · outbound

This paper cites Reddi, Satyen Kale, and Sanjiv Kumar.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Reddi, Satyen Kale, and Sanjiv Kumar

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.240134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55439c21-c60a-4862-b0d8-b1cd9351a48f · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions U-net: Convolutional networks for biomedical image segmentation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.243914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8db62c1b-d53e-4db1-9da9-2365708b94d5 · outbound

This paper cites Imagenet large scale visual recognition challenge.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Imagenet large scale visual recognition challenge

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.643699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b1ecd16c-31be-4878-aabb-41d0e4714c21 · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.629133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8fab1bdb-f194-4d08-9abb-3c92c97efde3 · outbound

This paper cites Rigid-motion scattering for image classiﬁca- tion.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Rigid-motion scattering for image classiﬁca- tion

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.614890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 357e9a92-d058-4791-84b0-312b77e27b09 · outbound

This paper cites Very deep convo- lutional networks for large-scale image recognition.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Very deep convo- lutional networks for large-scale image recognition

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.259312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f21952c-6e72-4429-af93-e988d28b5ea8 · outbound

This paper cites Igcv3: Interleaved low-rank group convolutions for efﬁcient deep neural networks.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Igcv3: Interleaved low-rank group convolutions for efﬁcient deep neural networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.590729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5f2c690a-0f2f-4d30-9958-4afeba87f194 · outbound

This paper cites Going deeper with convolutions.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Going deeper with convolutions

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.268127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7dd5dc6-e5a8-406c-b440-7809ce088bcd · outbound

This paper cites Rethinking the inception architecture for computer vision.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Rethinking the inception architecture for computer vision

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.564230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 53acad45-dd2a-4ea8-956b-b2311a036e12 · outbound

This paper cites Im- proving the speed of neural networks on cpus.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Im- proving the speed of neural networks on cpus

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.549192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3f160b91-6109-4979-9269-5e1ca37a4374 · outbound

This paper cites Factorized convolutional neural networks.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Factorized convolutional neural networks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.533807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0653df77-1c67-4ac7-bd79-75cebf4c4b69 · outbound

This paper cites Wang, Xiang Li, and Charles X.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Wang, Xiang Li, and Charles X

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.520569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d2a824fe-efe4-4f7e-8ba1-777dd958e9a5 · outbound

This paper cites Interleaved structured sparse convolutional neural networks.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Interleaved structured sparse convolutional neural networks

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.506351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 477db6dd-973b-4aae-a69e-183651a9b298 · outbound

This paper cites Aggregated residual transformations for deep neural networks.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Aggregated residual transformations for deep neural networks

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.293943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 406b5e60-921c-4024-9e69-7ef6166583aa · outbound

This paper cites In- terleaved group convolutions.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions In- terleaved group convolutions

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.481560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e107b68d-8024-49cd-84fd-b3fe88e12215 · outbound

This paper cites Shufﬂenet: An extremely efﬁcient convolutional neural net- work for mobile devices.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Shufﬂenet: An extremely efﬁcient convolutional neural net- work for mobile devices

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.302992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e92084e-e42d-4a07-af74-1fbbfa19d88d · outbound

This paper cites Scalable person re-identiﬁcation: A benchmark.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Scalable person re-identiﬁcation: A benchmark

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.307249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b52dba1-8c76-4b97-b43b-50992cdb2f69 · outbound

This paper cites Incremental network quantization: Towards lossless cnns with low-precision weights.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Incremental network quantization: Towards lossless cnns with low-precision weights

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.447485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3040dc99-f1dd-4f29-bff6-27e5b55e0d84 · outbound

This paper cites Explicit loss-error-aware quantization for low-bit deep neu- ral networks.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Explicit loss-error-aware quantization for low-bit deep neu- ral networks

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:03:09.433162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 70e7ea0a-7947-4e2b-9b7b-d2f64de01a12 · outbound

This paper cites Neural architecture search with reinforcement learning.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions Neural architecture search with reinforcement learning

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-14T14:03:09.319039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.