Paper Citation Record · LEDGER

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study

As of 12 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2412.06272.

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

pith.paper-citation-record.v1
2412.06272 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:55:14.151821Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

verified exact3
verified fuzzy0
unresolved33
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ad00ddbf-4081-42a4-95b8-309750578c19 · outbound

This paper cites GPT-4 Technical Report.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:13.877911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25bad4a2-cf7c-4847-8378-63541e9c2185 · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:13.885150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84986135-cd0d-4a6d-a918-63fcd4f7e71d · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:55:15.444772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8477b87d-23f8-44fb-9635-00f7f8cd820f · outbound

This paper cites BLT: Can Large Language Models Handle Basic Legal Text?.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study BLT: Can Large Language Models Handle Basic Legal Text?

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:55:15.081906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b84dc9b6-f0d3-4bdd-9889-9b4b698ff63e · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:13.917269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27bbb9ac-3d54-47c6-a102-641e8864e58d · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:13.924362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0609b96e-2a31-4c1a-8375-25604064a651 · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:55:15.404242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c71d5021-d4d5-4ae9-826c-8c3a0534d8b2 · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:55:15.378483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7fd9edda-af20-4558-89c2-4279a59918e2 · outbound

This paper cites SaulLM-7B: A pioneering Large Language Model for Law.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study SaulLM-7B: A pioneering Large Language Model for Law

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:13.944333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eebd91a3-50a2-48a5-bdfc-49bac44e6e18 · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:55:15.350333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6db59eec-60b3-48b8-b0c2-46babcf0a1fe · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:55:15.315279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e3fadae9-39c8-4af9-9607-9aa681c7478f · outbound

This paper cites Lawma: The Power of Specialization for Legal Annotation.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Lawma: The Power of Specialization for Legal Annotation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:13.964351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b6c4b9f-557f-413c-b500-44d1d9e1c34f · outbound

This paper cites LawBench: Benchmarking Legal Knowledge of Large Language Models.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:13.971200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 795e6d99-f7f4-4e7f-85f7-6d4604d8bf95 · outbound

This paper cites The Llama 3 Herd of Models.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study The Llama 3 Herd of Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:13.976720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29a8150a-5cf8-441e-a434-7c6a216c65e5 · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:55:15.283544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8e0bbbf1-a94d-4cac-bc44-07f8ce159b17 · outbound

This paper cites CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:13.987950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c5ff5a2-1119-413d-9d16-7f1b2524c21f · outbound

This paper cites A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:13.995166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d235d13-40d7-4f81-9988-8c320192b65f · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:55:15.262407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ccad2d1d-d9a7-4753-b7eb-ad374ee5796d · outbound

This paper cites CLERC: A Dataset for Legal Case Retrieval and Retrieval-Augmented Analysis Generation.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study CLERC: A Dataset for Legal Case Retrieval and Retrieval-Augmented Analysis Generation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.020826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0677367e-3c7b-4986-b064-5822be78bbaa · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen - Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen - Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.030703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af55a9b1-74ac-4c52-9607-945281bba414 · outbound

This paper cites Fine-tuning Large Language Models for Improving Factuality in Legal Question Answering.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Fine-tuning Large Language Models for Improving Factuality in Legal Question Answering

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:55:14.847761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e1874f82-5bfd-418b-8438-c54db42fe542 · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.043902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16bf2114-f5e8-4e5a-8e98-6186fae4784a · outbound

This paper cites IL-TUR: Benchmark for Indian Legal Text Understanding and Reasoning.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study IL-TUR: Benchmark for Indian Legal Text Understanding and Reasoning

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:55:14.720040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ca4500ef-cab4-4921-879b-208520ab91a9 · outbound

This paper cites LegalAgentBench: Evaluating LLM Agents in Legal Domain.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.057214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a77e2aa-7058-4fc2-b486-45db849e81c4 · outbound

This paper cites LexEval: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language Models.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study LexEval: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.065633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0faa0c98-400c-4f92-949d-5b13f0a585ea · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.072967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fe9db50-33bc-45e4-b6c5-650e2efcd91e · outbound

This paper cites Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.082869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e19084b3-af25-40f7-b273-ebabc9c8d899 · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.091292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32bbf20c-4f30-44ec-b552-0afdc4a976b8 · outbound

This paper cites Athena: Retrieval-augmented Legal Judgment Prediction with Large Language Models.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Athena: Retrieval-augmented Legal Judgment Prediction with Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.097181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8aa07e33-cd1b-4ed6-87fa-723b1166639e · outbound

This paper cites LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.103552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b737d79b-35fc-4efe-a0ba-7db34052b28f · outbound

This paper cites Legal Summarisation through LLMs: The PRODIGIT Project.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Legal Summarisation through LLMs: The PRODIGIT Project

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.110159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d6d56de-ffb3-403e-a188-a4b64a5ce441 · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:55:15.177004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dd27ec46-d08c-4494-8dee-b35a9830d3ac · outbound

This paper cites an unresolved cited work.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.123165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16793eed-f4fc-415e-8e9e-e79f3e0eb4e4 · outbound

This paper cites MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.129045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99f1039c-8b79-41e5-b9d0-f80c1f572444 · outbound

This paper cites online" 'onlinestring :=.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study online" 'onlinestring :=

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.142191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e15e7976-081c-42be-81c6-6d94934f3c05 · outbound

This paper cites write newline.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study write newline

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.151821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.