Paper Citation Record · LEDGER

Towards an Optimal Control Perspective of ResNet Training

As of 19 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 1 inbound Pith citation observation for arXiv:2506.21453.

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

pith.paper-citation-record.v1
2506.21453 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:33:20.307766Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T08:36:19.409783Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

verified exact1
verified fuzzy11
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e5442953-7ec8-4513-98b8-5385ccbd9414 · outbound

This paper cites Reversible architectures for arbitrarily deep residual neural networks.

Towards an Optimal Control Perspective of ResNet Training Reversible architectures for arbitrarily deep residual neural networks

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:33:21.945149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6ff093f2-9e48-40b8-ab91-8c8f4c4c8972 · outbound

This paper cites Sparsity in long-time control of neural odes.

Towards an Optimal Control Perspective of ResNet Training Sparsity in long-time control of neural odes

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:33:21.842127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 19452589-826e-48a9-879b-6fa89cf72481 · outbound

This paper cites Large-time asymptotics in deep learning.

Towards an Optimal Control Perspective of ResNet Training Large-time asymptotics in deep learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T22:33:19.403423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a4f22d7-fa8f-44c1-b134-bd7e920e387d · outbound

This paper cites On the turnpike to design of deep neural networks: Explicit depth bounds.

Towards an Optimal Control Perspective of ResNet Training On the turnpike to design of deep neural networks: Explicit depth bounds

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:33:21.751584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 96fdca18-8361-4272-85c8-ee8a9996fd49 · outbound

This paper cites Identity mappings in deep residual networks.

Towards an Optimal Control Perspective of ResNet Training Identity mappings in deep residual networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:33:21.637707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8c4feaf6-7a01-4188-a64e-c261f0aa5b97 · outbound

This paper cites Deep residual learning for image recognition.

Towards an Optimal Control Perspective of ResNet Training Deep residual learning for image recognition

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T22:33:19.634440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc70cedb-af93-4b38-a639-b57500a7fae8 · outbound

This paper cites Learning multiple layers of features from tiny images.

Towards an Optimal Control Perspective of ResNet Training Learning multiple layers of features from tiny images

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:33:21.545409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c5c823f0-31fe-4c3c-8dd7-b5f6957ff510 · outbound

This paper cites Lecun, L.

Towards an Optimal Control Perspective of ResNet Training Lecun, L

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T22:33:19.771337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd5a6d0a-5122-44a7-9422-7fea4042bba4 · outbound

This paper cites Deeply- Supervised Nets.

Towards an Optimal Control Perspective of ResNet Training Deeply- Supervised Nets

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:33:21.388829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 63fd83aa-528b-415d-83a3-b851ad90cfc1 · outbound

This paper cites Split computing and early exiting for deep learning applications: Survey and research challenges.

Towards an Optimal Control Perspective of ResNet Training Split computing and early exiting for deep learning applications: Survey and research challenges

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:33:21.219259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8e5639ee-8249-4717-895e-86dfd1cd8f0a · outbound

This paper cites How deep do we need: Accelerating training and inference of neural ODEs via control perspective.

Towards an Optimal Control Perspective of ResNet Training How deep do we need: Accelerating training and inference of neural ODEs via control perspective

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:33:20.998207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a3dc5027-1d47-46d3-be8e-3c38fad08822 · outbound

This paper cites On Dissipativity of Cross-Entropy Loss in Training ResNets.

Towards an Optimal Control Perspective of ResNet Training On Dissipativity of Cross-Entropy Loss in Training ResNets

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:33:20.478171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0c122b96-2697-4eaa-895d-d96d8298934b · outbound

This paper cites Pacheco, and Rodrigo S.

Towards an Optimal Control Perspective of ResNet Training Pacheco, and Rodrigo S

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:33:20.859435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 57bdc388-05b8-430a-a840-270b0749d97a · outbound

This paper cites Hence, the ResNet-54 in this paper corresponds to the ResNet-110 in [ 5].

Towards an Optimal Control Perspective of ResNet Training Hence, the ResNet-54 in this paper corresponds to the ResNet-110 in [ 5]

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:33:20.716693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4f71c0cb-9c45-42de-b91d-4e2eed827b6a · outbound

This paper cites 10 TOWARDS AN OPTIMAL CONTROL PERSPECTIVE OF RESNET TRAINING for all k = 0, ..., N.

Towards an Optimal Control Perspective of ResNet Training 10 TOWARDS AN OPTIMAL CONTROL PERSPECTIVE OF RESNET TRAINING for all k = 0, ..., N

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:33:20.596668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 55b42a6d-fe01-49fe-b130-acd556abadb7 · inbound

Exact ensemble controllability for neural differential equations via neural interpolation cites this paper.

Exact ensemble controllability for neural differential equations via neural interpolation Towards an Optimal Control Perspective of ResNet Training

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T08:36:19.409783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.