Paper Citation Record · LEDGER

Understanding plasticity in neural networks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2303.01486.

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

pith.paper-citation-record.v1
2303.01486 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:48:49.023177Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:38:55.627981Z

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 0c5f61b8-a66c-4923-a626-748f3e6bdea9 · inbound

How Should We Meta-Learn Reinforcement Learning Algorithms? cites this paper.

How Should We Meta-Learn Reinforcement Learning Algorithms? Understanding plasticity in neural networks

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T14:48:49.023177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ddabb7a-63c1-4621-b418-2853c550c589 · inbound

Plasticity-Enhanced Multi-Agent Mixture of Experts for Dynamic Objective Adaptation in UAVs-Assisted Emergency Communication Networks cites this paper.

Plasticity-Enhanced Multi-Agent Mixture of Experts for Dynamic Objective Adaptation in UAVs-Assisted Emergency Communication Networks Understanding plasticity in neural networks

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:55:58.953433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d8f1fadd-0ab0-467c-95d8-e45649d4266f · inbound

Rotation-Preserving Supervised Fine-Tuning cites this paper.

Rotation-Preserving Supervised Fine-Tuning Understanding plasticity in neural networks

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:27:24.416283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 66413e34-8b5c-47ce-85a1-e25759c2a5a6 · inbound

SFT Overtraining Predicts Rank Inversion via Entropy Collapse Under RLVR cites this paper.

SFT Overtraining Predicts Rank Inversion via Entropy Collapse Under RLVR Understanding plasticity in neural networks

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T20:38:55.629296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9cf61bb4-331d-4fd5-915e-e24e1cadee56 · inbound

Agentic Safety is an Epistemic Property, Not a Behavioral One cites this paper.

Agentic Safety is an Epistemic Property, Not a Behavioral One Understanding plasticity in neural networks

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-06-30T11:04:37.524271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d801293b-ec87-4ea3-80f9-2314d7b96f16 · inbound

Pessimism's Paradox: Conservative Offline Training Amplifies Reward Hacking During Online Adaptation in Reasoning Models cites this paper.

Pessimism's Paradox: Conservative Offline Training Amplifies Reward Hacking During Online Adaptation in Reasoning Models Understanding plasticity in neural networks

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T06:54:21.014641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.