Paper Citation Record · LEDGER

A study on the plasticity of neural networks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2106.00042.

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

pith.paper-citation-record.v1
2106.00042 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:07:24.494023Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T18:03:18.110250Z

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 45d7087c-0ed8-493e-bac8-eb76804204d0 · inbound

Plasticity Loss in Deep Reinforcement Learning: A Survey cites this paper.

Plasticity Loss in Deep Reinforcement Learning: A Survey A study on the plasticity of neural networks

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-23T18:03:18.113345Z

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 c49b059f-2ede-4824-b1ea-b1fc61245a3d · inbound

Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn cites this paper.

Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn A study on the plasticity of neural networks

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T12:07:24.494023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3718954-094b-45de-a396-ac95505cd461 · inbound

The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks cites this paper.

The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks A study on the plasticity of neural networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T11:10:51.302257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01d0f2ec-79f5-4145-b157-3ade2b71059c · inbound

Recovering Plasticity of Neural Networks via Soft Weight Rescaling cites this paper.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling A study on the plasticity of neural networks

Reference 1996

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:22.571278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1aeb29c1-86ab-46e9-bfd4-9cd57ab1f937 · inbound

A Simple Baseline for Stable and Plastic Neural Networks cites this paper.

A Simple Baseline for Stable and Plastic Neural Networks A study on the plasticity of neural networks

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:25.833464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e405dd8-937d-4655-8800-21991b0fed16 · inbound

Activation Function Design Sustains Plasticity in Continual Learning cites this paper.

Activation Function Design Sustains Plasticity in Continual Learning A study on the plasticity of neural networks

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T13:01:23.572077Z

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 7a23901f-0615-4350-9c48-7b1c2171a936 · inbound

Weight Decay Improves Language Model Plasticity cites this paper.

Weight Decay Improves Language Model Plasticity A study on the plasticity of neural networks

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-03T00:15:37.273732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.