Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Building a Subspace of Policies for Scalable Continual Learning
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2211.10445.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:18:39.117624Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T00:02:25.436461Z
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 e58bb50c-5338-4da9-a3e7-54726ced6629 · inbound
Advancements and Challenges in Continual Reinforcement Learning: A Comprehensive Review cites this paper.
Advancements and Challenges in Continual Reinforcement Learning: A Comprehensive Review Building a Subspace of Policies for Scalable Continual Learning
Reference 4309
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:18:39.117624Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 955eaa68-913c-4aec-a5bf-4394259d6f59 · inbound
A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.
A Survey of Reinforcement Learning for Large Reasoning Models Building a Subspace of Policies for Scalable Continual Learning
Reference 157
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T00:02:25.438764Z
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 f9e54f64-4e99-402e-bfd0-45e05fbcf66c · inbound
From Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning Environments cites this paper.
From Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning Environments Building a Subspace of Policies for Scalable Continual Learning
Reference 199
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T01:23:27.259408Z
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 d09e928a-6342-441d-9fc4-180b22d8f06d · inbound
Beyond Single-Model Optimization: Preserving Plasticity in Continual Reinforcement Learning cites this paper.
Beyond Single-Model Optimization: Preserving Plasticity in Continual Reinforcement Learning Building a Subspace of Policies for Scalable Continual Learning
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T11:05:08.931329Z
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 dff30a91-3157-46fd-b1ad-307b142c05e2 · inbound
Beyond Single-Model Optimization: Preserving Plasticity in Continual Reinforcement Learning cites this paper.
Beyond Single-Model Optimization: Preserving Plasticity in Continual Reinforcement Learning Building a Subspace of Policies for Scalable Continual Learning
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T19:46:39.624903Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.