Paper Citation Record · LEDGER

Learning to Optimize Neural Nets

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:1703.00441.

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

pith.paper-citation-record.v1
1703.00441 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:36:26.075291Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T12:05:38.302341Z

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 a51cfc6f-5e4b-4f2d-921c-c5d8f1cb5764 · inbound

Language Models are Few-Shot Learners cites this paper.

Language Models are Few-Shot Learners Learning to Optimize Neural Nets

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-07-04T22:22:44.583155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 45f2c938-2447-4218-ba68-daee2ae32aaa · inbound

Learning to Generate Gradients for Test-Time Adaptation via Test-Time Training Layers cites this paper.

Learning to Generate Gradients for Test-Time Adaptation via Test-Time Training Layers Learning to Optimize Neural Nets

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T06:05:35.791026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce83794c-4505-46c0-a53a-f987f6f4552a · 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 Learning to Optimize Neural Nets

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.399009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85686bdc-56fc-401b-83a6-9c64d3668046 · inbound

Improving Learning to Optimize Using Parameter Symmetries cites this paper.

Improving Learning to Optimize Using Parameter Symmetries Learning to Optimize Neural Nets

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-16T11:36:26.075291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8053e71d-e278-445f-af07-bc0c1f9267d2 · inbound

QuickSplat: Fast 3D Surface Reconstruction via Learned Gaussian Initialization cites this paper.

QuickSplat: Fast 3D Surface Reconstruction via Learned Gaussian Initialization Learning to Optimize Neural Nets

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T23:07:44.675840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f998e8fe-af3c-4a9c-9893-69e6a9366d7d · inbound

Deciphering Trajectory-Aided LLM Reasoning: An Optimization Perspective cites this paper.

Deciphering Trajectory-Aided LLM Reasoning: An Optimization Perspective Learning to Optimize Neural Nets

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T14:13:07.379623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55dcbe23-35b3-4071-878b-61e6cbc04c9f · inbound

Thinking Out of the Box: Hybrid SAT Solving by Unconstrained Continuous Optimization cites this paper.

Thinking Out of the Box: Hybrid SAT Solving by Unconstrained Continuous Optimization Learning to Optimize Neural Nets

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:08:47.428081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 557f8ec7-1fcf-4ff1-9eed-50071332bd96 · inbound

MatRL: Provably Generalizable Iterative Algorithm Discovery via Monte-Carlo Tree Search cites this paper.

MatRL: Provably Generalizable Iterative Algorithm Discovery via Monte-Carlo Tree Search Learning to Optimize Neural Nets

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T20:11:20.638117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74f78755-b27a-4131-95aa-e9507649e486 · inbound

Learning a Zeroth-Order Optimizer for Fine-Tuning LLMs cites this paper.

Learning a Zeroth-Order Optimizer for Fine-Tuning LLMs Learning to Optimize Neural Nets

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T13:28:47.435267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97e1c20c-1a10-492d-bc04-a417a99f2a67 · inbound

Greedy dynamical meta-learning cites this paper.

Greedy dynamical meta-learning Learning to Optimize Neural Nets

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-31T23:37:13.362586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.