Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Reverse Forward Curriculum Learning for Extreme Sample and Demonstration Efficiency in Reinforcement Learning
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.03379.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:53:28.697223Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T03:56:34.482592Z
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 f9041b35-fe36-4577-a0a7-77816c98da68 · inbound
Umbrella Reinforcement Learning -- computationally efficient tool for hard non-linear problems cites this paper.
Umbrella Reinforcement Learning -- computationally efficient tool for hard non-linear problems Reverse Forward Curriculum Learning for Extreme Sample and Demonstration Efficiency in Reinforcement Learning
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:35:45.074234Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 562cef5c-f270-45ac-8046-207313ef9b73 · inbound
Improving RL Exploration for LLM Reasoning through Retrospective Replay cites this paper.
Improving RL Exploration for LLM Reasoning through Retrospective Replay Reverse Forward Curriculum Learning for Extreme Sample and Demonstration Efficiency in Reinforcement Learning
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:53:28.697223Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fdc72d82-9b5d-48c6-8330-aefb0765e129 · inbound
RL-AWB: Deep Reinforcement Learning for Auto White Balance Correction in Low-Light Night-time Scenes cites this paper.
RL-AWB: Deep Reinforcement Learning for Auto White Balance Correction in Low-Light Night-time Scenes Reverse Forward Curriculum Learning for Extreme Sample and Demonstration Efficiency in Reinforcement Learning
Reference 94
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T16:01:04.868089Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c4ac3ab4-8416-4ce7-887f-fcfad2b2d1bf · inbound
RL-AWB: Deep Reinforcement Learning for Auto White Balance Correction in Low-Light Night-time Scenes cites this paper.
RL-AWB: Deep Reinforcement Learning for Auto White Balance Correction in Low-Light Night-time Scenes Reverse Forward Curriculum Learning for Extreme Sample and Demonstration Efficiency in Reinforcement Learning
Reference 94
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T11:45:48.257111Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0c8de6f1-10ec-417d-a70e-740d73c36887 · inbound
Grasp-Then-Plan with Failure Attribution: A Closed Two-Stage Framework for Precise and Generalizable Robotic Manipulation cites this paper.
Grasp-Then-Plan with Failure Attribution: A Closed Two-Stage Framework for Precise and Generalizable Robotic Manipulation Reverse Forward Curriculum Learning for Extreme Sample and Demonstration Efficiency in Reinforcement Learning
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T03:56:34.484094Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.