Paper Citation Record · LEDGER

When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2104.08671.

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

pith.paper-citation-record.v1
2104.08671 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:59:05.133607Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

14
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2af8c56e-2769-45c2-bcc7-572af90dfbc6 · inbound

Exploring How LLMs Capture and Represent Domain-Specific Knowledge cites this paper.

Exploring How LLMs Capture and Represent Domain-Specific Knowledge When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset

Reference 2017

Resolution: malformed identifier; no resolver link, observed 2026-08-16T10:59:05.133607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cb974e2-e372-4204-9fb7-045310b7c20d · inbound

Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization cites this paper.

Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:47.005670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f4172b4-8a77-45ff-a096-69ff94206d89 · inbound

How Can AI Augment Access to Justice? Public Defenders' Perspectives on AI Adoption cites this paper.

How Can AI Augment Access to Justice? Public Defenders' Perspectives on AI Adoption When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset

Reference 117

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:00:50.802144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 68a7b409-75c8-4469-a9c1-80b309a2ab9a · inbound

How Can AI Augment Access to Justice? Public Defenders' Perspectives on AI Adoption cites this paper.

How Can AI Augment Access to Justice? Public Defenders' Perspectives on AI Adoption When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-04T08:03:27.762295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7244b62-5825-4c51-b24d-52f1d5e2c366 · inbound

Learning When Not to Decide: A Framework for Overcoming Factual Presumptuousness in AI Adjudication cites this paper.

Learning When Not to Decide: A Framework for Overcoming Factual Presumptuousness in AI Adjudication When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-10T02:11:57.310682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation dc194b16-b498-454d-8acf-faa99c4d10f6 · inbound

Validate Your Authority: Benchmarking LLMs on Multi-Label Precedent Treatment Classification cites this paper.

Validate Your Authority: Benchmarking LLMs on Multi-Label Precedent Treatment Classification When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:28:16.558166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 346a0535-3d23-4de5-a8c5-dff737819500 · inbound

Legal Domain Adaptation of Modern BERT Models cites this paper.

Legal Domain Adaptation of Modern BERT Models When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:25:48.852599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.