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Paper Citation Record · LEDGER

Adaptive Training Distributions with Scalable Online Bilevel Optimization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.11973.

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

pith.paper-citation-record.v1
2311.11973 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:22:05.539480Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T14:36:36.967638Z

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 32456ea7-2e8e-48c4-99f9-cf9dad49440c · inbound

Lifting the Winding Number: Precise Discontinuities in Neural Fields for Physics Simulation cites this paper.

Lifting the Winding Number: Precise Discontinuities in Neural Fields for Physics Simulation Adaptive Training Distributions with Scalable Online Bilevel Optimization

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-09T18:22:05.539480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:22:05.539480Z digest=sha256:a4fc27f7b709308f083ade4165f082694d9aa9f04567ed061f9694b99f36d001

Observation 7351fd65-d779-4697-ba4c-ce4641107993 · inbound

Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining cites this paper.

Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining Adaptive Training Distributions with Scalable Online Bilevel Optimization

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-08T14:36:36.972736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T14:36:36.438299Z digest=sha256:a1b807ffad3fa10b1e2d1bfc0cdaeffd972f13661d5afab54f55abd1d4664109