Paper Citation Record · LEDGER

Neuroplastic Expansion in Deep Reinforcement Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.07994.

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

pith.paper-citation-record.v1
2410.07994 v3

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 2026-08-08T19:13:08.227488Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:30:06.971916Z

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 0fe1748a-cfcb-401a-b9ae-59d21b19a7ac · inbound

Growing with Experience: Growing Neural Networks in Deep Reinforcement Learning cites this paper.

Growing with Experience: Growing Neural Networks in Deep Reinforcement Learning Neuroplastic Expansion in Deep Reinforcement Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T04:08:35.146480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d32c5df-e889-44bd-8c6f-7f0abf8b5fbc · inbound

A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control cites this paper.

A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control Neuroplastic Expansion in Deep Reinforcement Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T20:31:07.804229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8f7f54c-368a-433f-a96d-98c13061d90b · inbound

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

A Simple Baseline for Stable and Plastic Neural Networks Neuroplastic Expansion in Deep Reinforcement Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:26.794741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 267c5868-d846-4f31-b5f4-d5187e45a199 · inbound

Forager: a lightweight testbed for continual learning with partial observability in RL cites this paper.

Forager: a lightweight testbed for continual learning with partial observability in RL Neuroplastic Expansion in Deep Reinforcement Learning

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:46:53.376780Z

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 c430aed2-42e7-4f88-a007-59cb2fe68240 · inbound

Stagnant Neuron: Towards Understanding the Plasticity Loss in Multi-Agent Reinforcement Learning Value Factorization Methods cites this paper.

Stagnant Neuron: Towards Understanding the Plasticity Loss in Multi-Agent Reinforcement Learning Value Factorization Methods Neuroplastic Expansion in Deep Reinforcement Learning

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-04T19:30:06.974571Z

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 cc8ed8f4-a625-4b49-ba79-bb78af8a0e3f · inbound

NeuMoSync: End-to-End Neuromodulatory Control for Plasticity and Adaptability in Continual Learning cites this paper.

NeuMoSync: End-to-End Neuromodulatory Control for Plasticity and Adaptability in Continual Learning Neuroplastic Expansion in Deep Reinforcement Learning

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-08T19:13:08.227488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.