Paper Citation Record · LEDGER

Bring Your Own Data! Self-Supervised Evaluation for Large Language Models

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2306.13651.

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

pith.paper-citation-record.v1
2306.13651 v2

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 2026-08-21T06:32:19.484+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T22:36:35.226801Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T04:13:52.538741Z

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 66c9d1d6-847e-490b-9b9c-80c427841ed6 · inbound

Baseline Defenses for Adversarial Attacks Against Aligned Language Models cites this paper.

Baseline Defenses for Adversarial Attacks Against Aligned Language Models Bring Your Own Data! Self-Supervised Evaluation for Large Language Models

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-13T23:24:40.143576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6f9a5829-ef34-4bf2-b5d0-3bb75e41c97a · inbound

Data-Centric Foundation Models in Computational Healthcare: A Survey cites this paper.

Data-Centric Foundation Models in Computational Healthcare: A Survey Bring Your Own Data! Self-Supervised Evaluation for Large Language Models

Reference 126

Resolution: verified exact; arxiv_id, observed 2026-05-24T04:13:52.542909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 175468ec-4f7d-45fd-8f04-b898cede2d09 · inbound

Benchmark Data Contamination of Large Language Models: A Survey cites this paper.

Benchmark Data Contamination of Large Language Models: A Survey Bring Your Own Data! Self-Supervised Evaluation for Large Language Models

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-22T23:10:40.993713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 648363cf-e420-45be-87f3-e164805f6cec · inbound

Verifiable Format Control for Large Language Model Generations cites this paper.

Verifiable Format Control for Large Language Model Generations Bring Your Own Data! Self-Supervised Evaluation for Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T22:36:35.226801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ff757e7-e5de-49e2-bc5b-8721fff27bb0 · inbound

Guardians and Offenders: A Survey on Harmful Content Generation and Safety Mitigation of LLM cites this paper.

Guardians and Offenders: A Survey on Harmful Content Generation and Safety Mitigation of LLM Bring Your Own Data! Self-Supervised Evaluation for Large Language Models

Reference 187

Resolution: unresolved; no resolver link, observed 2026-08-05T23:13:05.114655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.