Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Self-supervised Meta-Prompt Learning with Meta-Gradient Regularization for Few-shot Generalization
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2303.12314.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:23:12.546258Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T05:12:44.760231Z
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 2774d770-059e-47a3-b1ad-0b65c07fcf89 · inbound
FocusDiff: Advancing Fine-Grained Text-Image Alignment for Autoregressive Visual Generation through RL cites this paper.
FocusDiff: Advancing Fine-Grained Text-Image Alignment for Autoregressive Visual Generation through RL Self-supervised Meta-Prompt Learning with Meta-Gradient Regularization for Few-shot Generalization
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:23:12.546258Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 35383744-47a4-4262-8a60-eea83d4ecbb3 · inbound
What Limits Virtual Agent Application? OmniBench: A Scalable Multi-Dimensional Benchmark for Essential Virtual Agent Capabilities cites this paper.
What Limits Virtual Agent Application? OmniBench: A Scalable Multi-Dimensional Benchmark for Essential Virtual Agent Capabilities Self-supervised Meta-Prompt Learning with Meta-Gradient Regularization for Few-shot Generalization
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:02:29.236247Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4257cc99-784e-48f5-b5a3-a960acf0b048 · inbound
Towards Meta-Cognitive Knowledge Editing for Multimodal LLMs cites this paper.
Towards Meta-Cognitive Knowledge Editing for Multimodal LLMs Self-supervised Meta-Prompt Learning with Meta-Gradient Regularization for Few-shot Generalization
Reference 45
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T05:12:44.767507Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.