Paper Citation Record · LEDGER

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs

As of 4 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 1 inbound Pith citation observation for arXiv:2508.15989.

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

pith.paper-citation-record.v1
2508.15989 v2

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-18T21:22:53.964999Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T23:31:59.661576Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

13 of 13 outbound references displayed

verified exact7
verified fuzzy4
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a53e3d2a-0993-4a2e-a2f5-3adefccf10fa · outbound

This paper cites In 2023 32nd International Joint Conference on Artificial Intelligence (IJCAI).

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs In 2023 32nd International Joint Conference on Artificial Intelligence (IJCAI)

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T21:26:53.219746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1511dc74-38d2-4e6a-84fc-e64dce29ec7e · outbound

This paper cites an unresolved cited work.

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-05-18T21:26:53.216618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b987fb05-be1b-443e-b7ab-135d96e0087b · outbound

This paper cites Equilibrium Propagation with Continual Weight Updates.

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs Equilibrium Propagation with Continual Weight Updates

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-18T21:26:52.153507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 14b4e2b6-ebf6-4ea7-9f25-6971c5ce7e20 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs Gaussian Error Linear Units (GELUs)

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-18T21:26:52.148510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f421ae03-23b4-4149-b26d-927811182709 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs Distilling the Knowledge in a Neural Network

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-18T21:26:52.158333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ff3988b8-300a-4f18-ae02-1c42a4df60e3 · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-18T21:26:52.143672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f4ccbd87-fa54-4886-a847-ea5a8d9e3901 · outbound

This paper cites Some Fundamental Aspects about Lipschitz Continuity of Neural Networks.

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs Some Fundamental Aspects about Lipschitz Continuity of Neural Networks

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-18T21:26:52.132695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c6369615-a38a-4db3-bbf6-e7e1f83fea79 · outbound

This paper cites In 2024 International Conference on Neuromor- phic Systems (ICONS), 312–318.

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs In 2024 International Conference on Neuromor- phic Systems (ICONS), 312–318

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T21:26:53.209916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 82227b39-94b8-41bd-90b5-723ba7dd22c2 · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-18T21:26:52.127621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 82888637-1576-49ee-94b2-275e752577ae · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-18T21:26:52.138053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 22078810-623e-40e5-9973-54ea88a7301a · outbound

This paper cites In Medical image computing and computer-assisted intervention–MICCAI 2015: 18th international conference, Munich, Germany, October 5-9, 2015, proceedings, part III 18, 234–241.

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs In Medical image computing and computer-assisted intervention–MICCAI 2015: 18th international conference, Munich, Germany, October 5-9, 2015, proceedings, part III 18, 234–241

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T21:26:53.201998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 530d0b01-aac3-423b-a30a-499e6ab7c189 · outbound

This paper cites A Vanishing Gradient Problem In this section, Figure 5 demonstrates the neuron states within a VGG-13 trained by both the standard EP and aug- mented EP frameworks.

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs A Vanishing Gradient Problem In this section, Figure 5 demonstrates the neuron states within a VGG-13 trained by both the standard EP and aug- mented EP frameworks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T21:26:53.206010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d7562d45-9db8-41eb-8318-268bace32dfc · outbound

This paper cites an unresolved cited work.

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-05-18T21:26:53.213252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Pith citing papers

Observation 70f3e911-c87c-493d-a9cd-5d83cf4102ee · inbound

STAR: Astrocyte-Inspired State-Augmented Repair for Supervised Memristive AI Hardware Systems cites this paper.

STAR: Astrocyte-Inspired State-Augmented Repair for Supervised Memristive AI Hardware Systems Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T23:31:59.661576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.