Paper Citation Record · LEDGER

An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2308.00788.

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

pith.paper-citation-record.v1
2308.00788 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:33:54.796497Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T08:06:03.913777Z

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 81da3d96-286d-494d-a297-6e8f263c5d07 · inbound

Bayesian Reasoning for Physics Informed Neural Networks cites this paper.

Bayesian Reasoning for Physics Informed Neural Networks An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-05-24T08:06:03.916009Z

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 141ad7d3-e01b-4495-b403-50e15e80cb69 · inbound

Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives cites this paper.

Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T13:33:54.796497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b8b2e3c-fd41-43d3-b82b-4cba562abeee · inbound

Finding a Multiple Follower Stackelberg Equilibrium: A Fully First-Order Method cites this paper.

Finding a Multiple Follower Stackelberg Equilibrium: A Fully First-Order Method An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T21:22:14.195148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9e0bf03-e009-4b44-9754-7c68eefb0a6d · inbound

Bilevel Data Curation for LLM Fine-tuning: Offline Selection and Online Self-Refining Generation cites this paper.

Bilevel Data Curation for LLM Fine-tuning: Offline Selection and Online Self-Refining Generation An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-03T20:12:52.489056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfcfb241-87d2-4d5d-bca7-e1cf9961e377 · inbound

Bilevel learning cites this paper.

Bilevel learning An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:06:04.592608Z

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 56bc44e5-b218-4add-a951-e408d3597e03 · inbound

Optimization under Persistent State-Dependent Bias: Gradient-based Method and Complexity Analysis cites this paper.

Optimization under Persistent State-Dependent Bias: Gradient-based Method and Complexity Analysis An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning

Reference 199

Resolution: unresolved; no resolver link, observed 2026-08-01T00:57:20.638119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.