Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1910.07224.
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 2026-08-08T18:17:14.722731Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-08T18:17:30.040081Z
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 31e278d8-59ff-4bef-b480-28d1be6ddcbc · inbound
Improving Environment Novelty Quantification for Effective Unsupervised Environment Design cites this paper.
Improving Environment Novelty Quantification for Effective Unsupervised Environment Design Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments
Reference 40
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T18:17:30.047382Z
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 c6a5215c-499d-4598-a426-66dd4594c653 · inbound
Wiki-R1: Incentivizing Multimodal Reasoning for Knowledge-based VQA via Data and Sampling Curriculum cites this paper.
Wiki-R1: Incentivizing Multimodal Reasoning for Knowledge-based VQA via Data and Sampling Curriculum Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-07-15T14:43:21.866055Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.