Paper Citation Record · LEDGER

Meta-Learning with Implicit Gradients

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1909.04630.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1909.04630 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:23:55.785936Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T11:01:04.357666Z

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 01bd8cbe-d4af-4955-a407-bfeaf1b81cfd · inbound

MathPhys-Guided Coarse-to-Fine Anomaly Synthesis with SQE-Driven Bi-Level Optimization for Anomaly Detection cites this paper.

MathPhys-Guided Coarse-to-Fine Anomaly Synthesis with SQE-Driven Bi-Level Optimization for Anomaly Detection Meta-Learning with Implicit Gradients

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-16T12:23:55.785936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c0ff6ab-fdb7-4bdb-9f75-3a6ed5d01834 · inbound

A Discretization Approach for Bilevel Optimization with Low-Dimensional and Non-Convex Lower-Level cites this paper.

A Discretization Approach for Bilevel Optimization with Low-Dimensional and Non-Convex Lower-Level Meta-Learning with Implicit Gradients

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T21:12:38.904031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0947503-5305-4004-9491-ff345bdf26bc · inbound

Higher-Order Automatic Differentiation Using Symbolic Differential Algebra: Bridging the Gap between Algorithmic and Symbolic Differentiation cites this paper.

Higher-Order Automatic Differentiation Using Symbolic Differential Algebra: Bridging the Gap between Algorithmic and Symbolic Differentiation Meta-Learning with Implicit Gradients

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T12:01:20.406654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37e7c4b7-f3c1-46bc-a2e9-a0f3209d2ddf · inbound

Generalization Guarantees on Data-Driven Tuning of Gradient Descent with Langevin Updates cites this paper.

Generalization Guarantees on Data-Driven Tuning of Gradient Descent with Langevin Updates Meta-Learning with Implicit Gradients

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:01:04.363794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.