Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Single-Shot Pruning for Offline Reinforcement Learning
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2112.15579.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T19:16:28.873904Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T19:07:38.066874Z
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 5d17773e-dde5-4b96-925d-0897b0573e2e · inbound
Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity cites this paper.
Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity Single-Shot Pruning for Offline Reinforcement Learning
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:14:53.336007Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 147d1fd6-dcdf-41db-9ed7-45ea250aeecd · inbound
Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning cites this paper.
Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning Single-Shot Pruning for Offline Reinforcement Learning
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:16:28.873904Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 36385d74-c133-4369-81ba-6fef5e81fe05 · inbound
Exploring Sparse Adapters for Scalable Merging of Parameter Efficient Experts cites this paper.
Exploring Sparse Adapters for Scalable Merging of Parameter Efficient Experts Single-Shot Pruning for Offline Reinforcement Learning
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T19:07:38.097396Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.