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Paper Citation Record · LEDGER

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN)

As of 16 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:1908.03935.

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

pith.paper-citation-record.v1
1908.03935 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:00:47.613372Z

measured 20 of 20 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

20 of 20 outbound references displayed

  • verified exact2
  • verified fuzzy11
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f4cbef11-0beb-469c-9a29-093a4a36c31f · outbound

This paper cites GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism

Reference 1

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unresolved
no resolver link, observed 2026-08-14T14:00:47.542814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:00:47.542814Z digest=sha256:6ef66b931115d768822249539b69105ef7007d310d9c5f6a69b89aa5976f4336

Observation 0cbf2410-c8e1-4cf2-97e0-3bc902d21fe3 · outbound

This paper cites High performance training of deep neural networks using pipelined hardware acceleration and distributed memory,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) High performance training of deep neural networks using pipelined hardware acceleration and distributed memory,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-14T14:00:47.868806Z

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.

source=pdf_text observed=2026-08-14T14:00:47.547850Z digest=sha256:5f55954743ca07f10561e2518c83481a473c6e7d0839d33ebecd074700be2368

Observation f55b7c8e-5ed4-471e-be24-ab5f7cdcc455 · outbound

This paper cites Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis

Reference 3

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unresolved
no resolver link, observed 2026-08-14T14:00:47.552547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:00:47.552547Z digest=sha256:e7fb1d33e67a16141c9a66bd81527412984a7dc367038742a58bf6914585f23e

Observation e0776425-1d62-4854-b5a3-ec26dacb854b · outbound

This paper cites Beyond Data and Model Parallelism for Deep Neural Networks.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Beyond Data and Model Parallelism for Deep Neural Networks

Reference 4

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unresolved
no resolver link, observed 2026-08-14T14:00:47.557013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:00:47.557013Z digest=sha256:23e246a06abc0e5497d8e6d80a135761643f830cdd365c2344488d57a1823500

Observation 976a86fe-1da9-4a59-8cab-5f4800a0b0b2 · outbound

This paper cites The multi-lane capsule network,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) The multi-lane capsule network,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:00:47.857736Z

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.

source=pdf_text observed=2026-08-14T14:00:47.561406Z digest=sha256:9fdfcd7b5a6ce5b8416439d74b5a6a26586df0ce31b272592dbc960cea7b7ad9

Observation eb84a331-bb31-45ef-b7a4-aa3c7416cbdc · outbound

This paper cites Xception: Deep learning with depthwise separable convolu- tions,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Xception: Deep learning with depthwise separable convolu- tions,

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-14T14:00:47.565330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:00:47.565330Z digest=sha256:9a8758b0d69535f9467241acff370ad8ae6beba933825e3e0f2dac381364e6af

Observation c9ba4549-f0a7-4d2b-b924-64eb3d5d0fa2 · outbound

This paper cites Inception-v4, inception-resnet and the impact of residual connections on learning,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Inception-v4, inception-resnet and the impact of residual connections on learning,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:00:47.839465Z

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.

source=pdf_text observed=2026-08-14T14:00:47.569600Z digest=sha256:44a388ac75751a92352d689be90d2605ce73d7b15f880ac1a365f0ef26002d93

Observation fcde6916-bab4-4e59-9490-bcd4a49fa3ba · outbound

This paper cites Transforming auto- encoders,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Transforming auto- encoders,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:00:47.828732Z

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.

source=pdf_text observed=2026-08-14T14:00:47.573112Z digest=sha256:23f6d7dd8015588c42972b238754bf99a41de62cd29c8ad498d8692318d6bae7

Observation eda89c74-3a84-4eef-8c16-1012428b5ced · outbound

This paper cites Dynamic routing between capsules,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Dynamic routing between capsules,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:00:47.818943Z

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.

source=pdf_text observed=2026-08-14T14:00:47.576555Z digest=sha256:256a6cbf2afa37b7f27d8b71b7be4a3bddac41cf2fd2a65e0d95da347c2c06ac

Observation d3ddf990-a972-426e-a14f-421023f004a4 · outbound

This paper cites Improved Explainability of Capsule Networks: Relevance Path by Agreement.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Improved Explainability of Capsule Networks: Relevance Path by Agreement

Reference 10

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unresolved
no resolver link, observed 2026-08-14T14:00:47.580274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:00:47.580274Z digest=sha256:2330b92181803f1d12494cf8d987b746a2d2d41199f89b97918635783d4ffbe2

Observation dc2a1555-35d5-462b-acfb-10f13c8c5e4a · outbound

This paper cites Capsulegan: Generative adversarial capsule network,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Capsulegan: Generative adversarial capsule network,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:00:47.808649Z

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.

source=pdf_text observed=2026-08-14T14:00:47.584073Z digest=sha256:a527d4138f892f4fe10760f0b61b56e4c1bae8ca0f349df60818fa37c10f40c9

Observation 365a411c-6250-474a-9b1d-9469c92d2c18 · outbound

This paper cites Compositional Coding Capsule Network with K-Means Routing for Text Classification.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Compositional Coding Capsule Network with K-Means Routing for Text Classification

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-14T14:00:47.680475Z

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.

source=pdf_text observed=2026-08-14T14:00:47.587585Z digest=sha256:a32d5ff9480bc460ed01c41d45a73c29aaf482fecf766adcd72d51cd4aa83f7c

Observation 315fa440-04a7-436e-bd13-eb5f36f9652c · outbound

This paper cites Capsule networks against medical imaging data challenges,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Capsule networks against medical imaging data challenges,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:00:47.797486Z

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.

source=pdf_text observed=2026-08-14T14:00:47.590927Z digest=sha256:87598738be5e288e25abd56871b75936c34949bda47d213bd81f486ba4a85e91

Observation 346d7e56-8c1f-4552-b2f2-07c3f48e92d4 · outbound

This paper cites Fast CapsNet for Lung Cancer Screening.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Fast CapsNet for Lung Cancer Screening

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-14T14:00:47.663933Z

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.

source=pdf_text observed=2026-08-14T14:00:47.594010Z digest=sha256:821b88f3e7bce67ac24c29d597fae2e74511bf3cd350679c6e2c1cb05ec55799

Observation 34fb8847-61ec-4c92-8542-4198bae684a1 · outbound

This paper cites A capsule network for traffic speed prediction in complex road networks,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) A capsule network for traffic speed prediction in complex road networks,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:00:47.784464Z

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.

source=pdf_text observed=2026-08-14T14:00:47.597543Z digest=sha256:523fe5d216ba9d4e692b02115edb42b6612c7c0d6afd73b70e6b5c1bc9aa6b99

Observation 71b4f356-de62-412c-8530-3bcf8bbbaae5 · outbound

This paper cites CapsNet comparative performance evaluation for image classification.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) CapsNet comparative performance evaluation for image classification

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-14T14:00:47.600716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:00:47.600716Z digest=sha256:273a3d7d563f78c167ff378eef77aaab162ce033fda304b3ff7a07de51817545

Observation c7d63477-8d19-4598-af45-7e57e09939ec · outbound

This paper cites Ms-capsnet: A novel multi-scale capsule network,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Ms-capsnet: A novel multi-scale capsule network,

Reference 17

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unresolved
no resolver link, observed 2026-08-14T14:00:47.603947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:00:47.603947Z digest=sha256:e92e4e6f2a1daa1d2cde3ad99119a5473142e2691b2cb73278403a4d6be2b265

Observation 1edde92c-cdcf-4525-bef5-a3eb7836bee9 · outbound

This paper cites Path capsule networks,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Path capsule networks,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:00:47.765408Z

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.

source=pdf_text observed=2026-08-14T14:00:47.607196Z digest=sha256:5721a2249b3e1c5a47881628a702dbea60aa211e62ca66f7a74a507b9fc87e12

Observation 32abba1a-2fbc-443a-afbd-d5440f3aa590 · outbound

This paper cites Computing science: The easiest hard problem,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Computing science: The easiest hard problem,

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-14T14:00:47.753038Z

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.

source=pdf_text observed=2026-08-14T14:00:47.610293Z digest=sha256:136125b729da198019fdb69e8e41fb04d7afa0d07d0a3b4dea6d82eca027dfd0

Observation d054b754-f602-4baf-9aba-b5c772a87677 · outbound

This paper cites Multi-way number partitioning,.

Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN) Multi-way number partitioning,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:00:47.739829Z

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.

source=pdf_text observed=2026-08-14T14:00:47.613372Z digest=sha256:b626f449108ab4d8a7c9a968f72130c7837b2aa94953c2618cf6e0f2a7093a5d

Pith citing papers

No inbound Pith citation observations are available.