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Paper Citation Record · LEDGER

Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2009.11243.

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

pith.paper-citation-record.v1
2009.11243 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:35:46.475611Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:19:30.034335Z

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 cd516bb9-96a0-47d6-9402-4d43cbb745bc · inbound

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning cites this paper.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-10T17:35:46.475611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:35:46.475611Z digest=sha256:35533109d26935a40ae231f18ee46357ed3f7dd110e9ab1ec2a453b68e3fb7a9

Observation a7ead697-18fc-413d-bf75-9672ca8a29de · inbound

Celo: Training Versatile Learned Optimizers on a Compute Diet cites this paper.

Celo: Training Versatile Learned Optimizers on a Compute Diet Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T17:01:13.969069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:01:13.969069Z digest=sha256:b0dfefc00f286a550442c928fe336d36f61dd369c4356f4b7f0620fd29ca883d

Observation 44f62159-29b7-427f-9199-f6b3536a3d0c · inbound

How Should We Meta-Learn Reinforcement Learning Algorithms? cites this paper.

How Should We Meta-Learn Reinforcement Learning Algorithms? Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T14:48:49.605196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:48:49.605196Z digest=sha256:87592580b49c79dc8c74c43a70301fb4caa0d4b2c3774e282b855c2a7191cb2e

Observation 66849f39-ba42-4de8-81f2-0880973a415b · inbound

Learn2Splat: Extending the Horizon of Learned 3DGS Optimization cites this paper.

Learn2Splat: Extending the Horizon of Learned 3DGS Optimization Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-20T18:58:53.930645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-20T18:56:12.134306Z digest=sha256:659a894fef6e6bcbd12a65133c4cc451992d01263b7f829616267a724f95df9d

Observation 68a2e6ff-fda1-400c-95ab-e4e99d9a2d03 · inbound

FlowBender: Feedback-Aware Training for Self-Correcting Conditional Flows cites this paper.

FlowBender: Feedback-Aware Training for Self-Correcting Conditional Flows Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves

Reference 41

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T03:19:30.036596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-26T18:17:25.479543Z digest=sha256:64483ea45e3a3495e399a9feb6112189ccf4ecce18e5b2a580bf5fa59c23e8f5