Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Efficient Reinforcement Learning with Large Language Model Priors
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.07927.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:13:43.329899Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T17:50:00.073152Z
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 305b7bed-a869-4f01-8ebc-60d8f37803b9 · inbound
HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving cites this paper.
HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Efficient Reinforcement Learning with Large Language Model Priors
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:13:43.329899Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e3983245-fbc8-40f6-96d3-144f483723f9 · inbound
Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration cites this paper.
Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration Efficient Reinforcement Learning with Large Language Model Priors
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T09:16:04.481445Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 15f50169-fca5-4fc5-8757-d2b5660d27e8 · inbound
Reinforcement Learning Foundation Models Should Already Be A Thing cites this paper.
Reinforcement Learning Foundation Models Should Already Be A Thing Efficient Reinforcement Learning with Large Language Model Priors
Reference 21
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T23:39:05.095619Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b8d68713-0cc0-4e3e-aea3-c6ddf33b5067 · inbound
LaGO: Latent Action Guidance for Online Reinforcement Learning cites this paper.
LaGO: Latent Action Guidance for Online Reinforcement Learning Efficient Reinforcement Learning with Large Language Model Priors
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T17:50:00.074812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.