Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T01:03:47.009487Z
Paper Citation Record · LEDGER
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization
As of 20 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2505.02172.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-10T05:56:03.443358Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T05:56:10.838739Z
Reference resolution
26 of 26 outbound references displayed
- verified exact0
- verified fuzzy2
- unresolved24
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation e7662773-9bd5-420b-ac9f-f701756a5580 · outbound
This paper cites Language Models are Few-Shot Learners.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Language Models are Few-Shot Learners
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.927240Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ce7d747f-0a31-4707-9df2-1439966f55a5 · outbound
This paper cites LexGLUE: A Benchmark Dataset for Legal Language Understanding in English.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization LexGLUE: A Benchmark Dataset for Legal Language Understanding in English
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.930667Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 74a7b97c-742c-40ea-9c36-6477d43b32bc · outbound
This paper cites TEaR: Improving LLM-based Machine Translation with Systematic Self-Refinement.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization TEaR: Improving LLM-based Machine Translation with Systematic Self-Refinement
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.933753Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1dbbb37a-3f46-4787-bb49-11153728760b · outbound
This paper cites an unresolved cited work.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Unresolved cited work
Reference 4
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T01:03:47.191694Z
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 af9ad17c-8bfb-4823-b8ca-ea4ca7036b1b · outbound
This paper cites SoK: Memorization in General-Purpose Large Language Models.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization SoK: Memorization in General-Purpose Large Language Models
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.940372Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3df06d5b-ebd5-4425-a0b5-ab9d673f63a2 · outbound
This paper cites Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.944751Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 595dfe9b-34f4-4e52-b52e-b09614f93065 · outbound
This paper cites Scaling Laws for Neural Language Models.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Scaling Laws for Neural Language Models
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.947838Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bccc453a-365b-4f20-8f1f-43951f5270b0 · outbound
This paper cites Natural Language Processing in the Legal Domain.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Natural Language Processing in the Legal Domain
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.951310Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b40cdca-aaf9-4ac0-ac1a-7d0cb849c999 · outbound
This paper cites an unresolved cited work.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Unresolved cited work
Reference 9
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T01:03:47.184747Z
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 702b725f-940e-46d8-bbf7-bdc6862f12ed · outbound
This paper cites Mapping the Increasing Use of LLMs in Scientific Papers.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Mapping the Increasing Use of LLMs in Scientific Papers
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.957342Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a459f5d7-0655-495d-aac0-4f243828342a · outbound
This paper cites Mellinkoff.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Mellinkoff
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T01:03:47.176381Z
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 c899c309-f527-4cfa-a903-2646b7bbd87a · outbound
This paper cites an unresolved cited work.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T01:03:47.169070Z
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 df023593-d7b2-4afc-8be0-fb2f715d0866 · outbound
This paper cites MultiLegalPile: A 689GB Multilingual Legal Corpus.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization MultiLegalPile: A 689GB Multilingual Legal Corpus
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.968344Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a28bf9ce-488d-41ce-8fa0-76f21edf9e5c · outbound
This paper cites an unresolved cited work.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Unresolved cited work
Reference 14
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T01:03:47.161478Z
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 2f6ac44f-6c7c-4876-a851-45765cb51328 · outbound
This paper cites GPT-4o System Card.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization GPT-4o System Card
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.974539Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0442d9d6-3cfa-4a0e-8560-2f13e029f4d3 · outbound
This paper cites The Butterfly Effect of Altering Prompts: How Small Changes and Jailbreaks Affect Large Language Model Performance.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization The Butterfly Effect of Altering Prompts: How Small Changes and Jailbreaks Affect Large Language Model Performance
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.977332Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8ac6c14e-9e6f-4d55-b824-6570d9a155cc · outbound
This paper cites an unresolved cited work.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T01:03:47.153062Z
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 e3fe99b6-fdbe-4bcc-b80e-6bd01d71c96f · outbound
This paper cites Multi-LexSum: Real-World Summaries of Civil Rights Lawsuits at Multiple Granularities.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Multi-LexSum: Real-World Summaries of Civil Rights Lawsuits at Multiple Granularities
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.983777Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 275ad312-6be6-47de-aef8-9dacb1c38718 · outbound
This paper cites Exploring LLM Prompting Strategies for Joint Essay Scoring and Feedback Generation.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Exploring LLM Prompting Strategies for Joint Essay Scoring and Feedback Generation
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.987285Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 23ca2fc4-ce47-4f89-ba7f-d027c1a30309 · outbound
This paper cites an unresolved cited work.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Unresolved cited work
Reference 20
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T01:03:47.143403Z
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 4424d8c2-330c-479c-aa69-c38216b0dd87 · outbound
This paper cites William Webber.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization William Webber
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T01:03:47.136389Z
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 0257b87d-7546-4d85-8898-84cbd2b0ec43 · outbound
This paper cites an unresolved cited work.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Unresolved cited work
Reference 22
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T01:03:47.128215Z
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 45361f28-2410-4d73-820f-39cf9e38210d · outbound
This paper cites Planning In Natural Language Improves LLM Search For Code Generation.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Planning In Natural Language Improves LLM Search For Code Generation
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:46.999852Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d3d7a714-469e-4fbb-9875-c7b342703487 · outbound
This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:47.003194Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6cb974e2-e372-4204-9fb7-045310b7c20d · outbound
This paper cites When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset.
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 807c1731-f258-432a-ad80-5cf50c363cda · outbound
This paper cites Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis.
Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T01:03:47.009487Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation 01acb22b-9897-4f5e-badd-c9a066afb2f6 · inbound
Towards Intelligent Legal Document Analysis: CNN-Driven Classification of Case Law Texts cites this paper.
Towards Intelligent Legal Document Analysis: CNN-Driven Classification of Case Law Texts Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T05:56:10.840022Z
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.