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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 13 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 2026-08-13T06:32:02.005865+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

Reference 1

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:13.877911Z digest=sha256:5a7b9ad86410938f406c29342138c97f0839b101293e78fbbad8b766c1556a83

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:13.885150Z digest=sha256:8d61eace8c7ba175a898ebdbc21ec7454ec9b847ca140921f8d683deef1e0b78

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

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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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T19:55:13.891078Z digest=sha256:17ed1d6ad439898bcec3ad2d204e7be8b29c8c3e73327d6ad981ca72878362a9

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

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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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T19:55:13.910332Z digest=sha256:a60d982c7de55fc1f29bc73ed61ecc1e5662d7052419ed6b5ff0a03aeb3dd6bf

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:13.917269Z digest=sha256:be9e67ff8eed787cb25e11d7b3144c0804a4fce6b4a4eaf25b201392ab9f5114

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:13.924362Z digest=sha256:b123c69bfd24d3922f7170322aab0f0148546a8692843fce3f1c638fdd98afa5

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

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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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T19:55:13.930884Z digest=sha256:610cd22e9e868bfc6e8bb8fc70c6e27e9745d613080d38d605db91ce6b675152

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

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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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T19:55:13.938041Z digest=sha256:5d1169e35f204fdaa3d4fa880155a71416cdc7be230822738c9d960730662758

Reference 9

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:13.944333Z digest=sha256:1197ab8cdf61994a8fa829cbaa6b17af007f7458cf4fd513dc9fcf49ad0d1c2d

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

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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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T19:55:13.950941Z digest=sha256:6ff0e9a490552bc2b8cc2fd7ab71eb25a7398e4ae495dc0a3d43fa052a4230a5

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T19:55:13.958722Z digest=sha256:7266a4d34056349e63b6326ec05f11e5d1f4014aafa60e3c4e11f668a46118bb

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:13.964351Z digest=sha256:1d1f59f217b3cc79bf13a4ca069569de0211d96fede8aec3011104758d31f994

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:13.971200Z digest=sha256:2b9cb1f6c66c8470f1318bc93c47bfd66459b63c884d87bc0097fddda2f3acf8

Reference 14

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:13.976720Z digest=sha256:4b8a460b783cf96b002fbdfe3d5c4adda9b5fc75b69351cb44e84018bac75627

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T19:55:13.982293Z digest=sha256:83cc7f56c90ea07cfedf35f0d3d33d0412327681ad0ed8f3ae7a3e0776219a51

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:13.987950Z digest=sha256:6ede4f12aec0ea7c90f8f0d4b350a05cbdcada785e67f2c5557ed80bbc7f86d7

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:13.995166Z digest=sha256:04da4c3873f66fd45bf6a1c9da82ddeb22a14287f12a983eefa0ce6fbf5b10b0

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

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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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T19:55:14.009821Z digest=sha256:d2a89bd602ad2452449e72112cbf1dddc87856fb0f36e52566c4b935557d1298

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.020826Z digest=sha256:47be659ea1151106fd88f55cac3f25931c02c88708885fd3f3b828413b3549bd

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.030703Z digest=sha256:5cee5fa08cb2b91bc42fbe2e0715a30840918ddcdbd77a1de4b4aa0ae9aefd80

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

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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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T19:55:14.036760Z digest=sha256:476c12afbd4ed52ce9209b488b7e7bfa0b004a729fbc3dfb472d7d09b27c5966

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.043902Z digest=sha256:7c9e67f47ca4395c14772cba19457cdd46d48c4024e314020cd7d06ffa1afeba

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T19:55:14.050387Z digest=sha256:e88573ef118ee8bfea41069c19df155d4c80993a7ecb72fbd85b908b09f42d9e

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.057214Z digest=sha256:86f1741003ce5ff3d2bdf9c96a4f007a01abb4593a32f62a70853e4f19a70ae3

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.065633Z digest=sha256:802fdd8ed5c31fdcc70bfc5334ddc110b800da435665a28b51ee524b87ebea4b

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.072967Z digest=sha256:be1c2ffb27ac1c53071e076dd94a92920f538a4462ba5adc5f0ddeb071fafb2e

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.082869Z digest=sha256:d8ed37e8a0efea308e40de47709e9161aaf652a7d8832ded246788a0bcf5f0cc

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.091292Z digest=sha256:5916bfad11a2caf2550953c202060bb19a5dbe4c95b05dd71054aeee194d796a

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.097181Z digest=sha256:bd2639b967616a4a87b7b2c8f0f7bffa125615b2f415899a1dbf10ba99c5d6c8

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.103552Z digest=sha256:b7cdc6e345ce83539668d789b2b177e15b801f0df76f739e999070c254d3df49

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.110159Z digest=sha256:9692cdc3ee07caa8d34905d57c323e32980980eb1dd35943a2f350ac89708a2e

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T19:55:14.117465Z digest=sha256:e260a57a8b4d789e6af13cc6db437e944ff591b30d179cea33495cce2f4330b9

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.123165Z digest=sha256:ff39c3e539e4db7a728d8f9cc2a643caf40471466fc19add88942315cc23c143

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:55:14.129045Z digest=sha256:b28b0a6d65b667dbd6c43d6936dca67e08f2cac2fed5a7ee1bee6553de73f042

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.

source=arxiv_source observed=2026-08-11T19:55:14.142191Z digest=sha256:fb62df95d0828476f670f19fd17bd54cf9ca6d8f4f157f6592be6cdae6f0665e

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.

source=arxiv_source observed=2026-08-11T19:55:14.151821Z digest=sha256:cdc9b034c6aa228ed0f7af5cebee93164c612b2083e1aaa034c9910ff9cdbe1e

Pith citing papers

No inbound Pith citation observations are available.