Paper Citation Record · LEDGER

Gradient-based Bi-level Optimization for Deep Learning: A Survey

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2207.11719.

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

pith.paper-citation-record.v1
2207.11719 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:49:32.245069Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T19:22:34.802677Z

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 7a4fe3c5-57ca-4a87-bcc6-1536ca43ad24 · inbound

Investigating the Impact of Data Selection Strategies on Language Model Performance cites this paper.

Investigating the Impact of Data Selection Strategies on Language Model Performance Gradient-based Bi-level Optimization for Deep Learning: A Survey

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T21:49:32.245069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bac9eeaa-23ad-400b-8e3a-0ceee9d7fe4f · inbound

Commute Your Domains: Trajectory Optimality Criterion for Multi-Domain Learning cites this paper.

Commute Your Domains: Trajectory Optimality Criterion for Multi-Domain Learning Gradient-based Bi-level Optimization for Deep Learning: A Survey

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T14:26:11.709561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7871e62a-ed22-48c5-a5aa-b83a097be21a · inbound

AffinityFlow: Guided Flows for Antibody Affinity Maturation cites this paper.

AffinityFlow: Guided Flows for Antibody Affinity Maturation Gradient-based Bi-level Optimization for Deep Learning: A Survey

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T18:32:13.827628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccc06cb3-b767-4221-bfb0-141fc500e778 · inbound

Cellular Traffic Prediction via Byzantine-robust Asynchronous Federated Learning cites this paper.

Cellular Traffic Prediction via Byzantine-robust Asynchronous Federated Learning Gradient-based Bi-level Optimization for Deep Learning: A Survey

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:50.238544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 534cf64d-9d93-4bf7-84a8-5ef277a4b5ac · inbound

AdaDeDup: Adaptive Hybrid Data Pruning for Efficient Large-Scale Object Detection Training cites this paper.

AdaDeDup: Adaptive Hybrid Data Pruning for Efficient Large-Scale Object Detection Training Gradient-based Bi-level Optimization for Deep Learning: A Survey

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T23:05:17.754757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 606b3050-463d-45e8-89bd-deb71b8b5040 · inbound

Synergistic Localization and Sensing in MIMO-OFDM Systems via Mixed-Integer Bilevel Learning cites this paper.

Synergistic Localization and Sensing in MIMO-OFDM Systems via Mixed-Integer Bilevel Learning Gradient-based Bi-level Optimization for Deep Learning: A Survey

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T19:51:16.769837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6ae1584-aa33-4cb8-ab4e-b336c635d515 · inbound

CHAL: Council of Hierarchical Agentic Language cites this paper.

CHAL: Council of Hierarchical Agentic Language Gradient-based Bi-level Optimization for Deep Learning: A Survey

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:59:25.710069Z

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 a8ab5bb8-452b-4867-b966-776e02bf83c7 · inbound

On the Difficulty of Learning a Meta-network for Training Data Selection cites this paper.

On the Difficulty of Learning a Meta-network for Training Data Selection Gradient-based Bi-level Optimization for Deep Learning: A Survey

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:22:34.804191Z

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.