Paper Citation Record · LEDGER

Deep Rewiring: Training very sparse deep networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:1711.05136.

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

pith.paper-citation-record.v1
1711.05136 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:34:36.831819Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-06-30T20:55:03.870346Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4427b678-abf1-4b92-9a2e-f7819cb2f4bf · inbound

QP-SNN: Quantized and Pruned Spiking Neural Networks cites this paper.

QP-SNN: Quantized and Pruned Spiking Neural Networks Deep Rewiring: Training very sparse deep networks

Reference 2005

Resolution: unresolved; no resolver link, observed 2026-08-08T17:34:36.831819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5193e021-c86b-4be2-8e41-7df1064721d2 · inbound

NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling cites this paper.

NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling Deep Rewiring: Training very sparse deep networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:44:12.035710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0e05dfe-9b20-4ddc-9a8a-5c264c44b39a · inbound

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum cites this paper.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Deep Rewiring: Training very sparse deep networks

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.112978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5494f077-b7c8-4fd4-a8c8-066f632b7ee0 · inbound

A Topological Improvement of the Overall Performance of Sparse Evolutionary Training: Motif-Based Structural Optimization of Sparse MLPs Project cites this paper.

A Topological Improvement of the Overall Performance of Sparse Evolutionary Training: Motif-Based Structural Optimization of Sparse MLPs Project Deep Rewiring: Training very sparse deep networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T04:59:47.620902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5649613-9af0-490d-aee7-85a81c5d09e0 · inbound

A Replicate-and-Quantize Strategy for Plug-and-Play Load Balancing of Sparse Mixture-of-Experts LLMs cites this paper.

A Replicate-and-Quantize Strategy for Plug-and-Play Load Balancing of Sparse Mixture-of-Experts LLMs Deep Rewiring: Training very sparse deep networks

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T21:32:44.948013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0aec166c-d924-46e0-9565-e6c144c4dca5 · inbound

On the Stability of Growth in Structural Plasticity cites this paper.

On the Stability of Growth in Structural Plasticity Deep Rewiring: Training very sparse deep networks

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-19T15:42:38.791728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 343ce45a-ffb5-487d-aa28-1f1090416f9c · inbound

On the Stability of Growth in Structural Plasticity cites this paper.

On the Stability of Growth in Structural Plasticity Deep Rewiring: Training very sparse deep networks

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-06-30T20:55:03.871741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a201f1ea-387f-4996-b2e0-c73d54bd2e5e · inbound

Synaptic clustering emerges from learning and supports covariance discrimination cites this paper.

Synaptic clustering emerges from learning and supports covariance discrimination Deep Rewiring: Training very sparse deep networks

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-31T13:05:04.964802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.