Paper Citation Record · LEDGER

Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 22 inbound Pith citation observations for arXiv:2405.20362.

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

pith.paper-citation-record.v1
2405.20362 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 22 of 22 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:14:08.202520Z

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

34
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 8a2568bd-c6e4-4cd4-a887-6594def60e28 · inbound

Enhancing Trust in Large Language Models via Uncertainty-Calibrated Fine-Tuning cites this paper.

Enhancing Trust in Large Language Models via Uncertainty-Calibrated Fine-Tuning Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-23T07:47:42.623972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 58d545f7-c9ce-41b9-ae12-21f89cc04be3 · inbound

BR-TaxQA-R: A Dataset for Question Answering with References for Brazilian Personal Income Tax Law, including case law cites this paper.

BR-TaxQA-R: A Dataset for Question Answering with References for Brazilian Personal Income Tax Law, including case law Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T15:14:08.202520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc7718ae-3a52-4b58-bc5d-186c6a6f41a7 · inbound

(Fact) Check Your Bias cites this paper.

(Fact) Check Your Bias Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T22:24:31.817701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88592164-dc94-4660-a785-89a870bd7950 · inbound

Loki's Dance of Illusions: A Comprehensive Survey of Hallucination in Large Language Models cites this paper.

Loki's Dance of Illusions: A Comprehensive Survey of Hallucination in Large Language Models Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 181

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:09.145901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 986fb662-d0f2-404d-a0ac-9ef238351b60 · inbound

The Consistency-Acceptability Divergence of LLMs in Judicial Decision-Making: Task and Stakeholder Dimensions cites this paper.

The Consistency-Acceptability Divergence of LLMs in Judicial Decision-Making: Task and Stakeholder Dimensions Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T18:39:05.738071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d789dc0d-b834-4f38-a93a-9143bbfff964 · inbound

Data and AI governance: Promoting equity, ethics, and fairness in large language models cites this paper.

Data and AI governance: Promoting equity, ethics, and fairness in large language models Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T01:03:22.236217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abce1450-8ff4-4cdd-bcac-665ba158290a · inbound

AI for Statutory Simplification: A Comprehensive State Legal Corpus and Labor Benchmark cites this paper.

AI for Statutory Simplification: A Comprehensive State Legal Corpus and Labor Benchmark Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T15:51:46.340003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef0499be-3b8a-4877-9ed1-01051cfdc52f · inbound

AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights cites this paper.

AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T13:38:53.703728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90f1e092-737f-441b-8a94-678715b651c4 · inbound

GrACE: A Generative Approach to Better Confidence Elicitation and Efficient Test-Time Scaling in Large Language Models cites this paper.

GrACE: A Generative Approach to Better Confidence Elicitation and Efficient Test-Time Scaling in Large Language Models Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-18T17:56:42.104825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2b180aa1-2396-4ba0-946e-141b44ad65a4 · inbound

Inteligencia Artificial jur\'idica y el desaf\'io de la veracidad: an\'alisis de alucinaciones, optimizaci\'on de RAG y principios para una integraci\'on responsable cites this paper.

Inteligencia Artificial jur\'idica y el desaf\'io de la veracidad: an\'alisis de alucinaciones, optimizaci\'on de RAG y principios para una integraci\'on responsable Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-04T19:07:42.718252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8acc4c9-1b58-432a-9832-34e869492103 · inbound

Linguistic Nepotism: Trading-off Quality for Language Preference in Multilingual RAG cites this paper.

Linguistic Nepotism: Trading-off Quality for Language Preference in Multilingual RAG Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-04T16:31:23.623820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 623d0ec4-81f8-4b76-8766-dc0b9177b224 · inbound

From Proof to Program: Characterizing Tool-Induced Reasoning Hallucinations in Large Language Models cites this paper.

From Proof to Program: Characterizing Tool-Induced Reasoning Hallucinations in Large Language Models Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:50:25.776509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 30eb3ce6-685c-4ad8-9630-bfe6edb0e470 · 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 Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T02:11:57.281802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0ebeec2b-cc9d-4804-bdcf-923de1abf639 · inbound

Expert Evaluation of LLM's Open-Ended Legal Reasoning on the Japanese Bar Exam Writing Task cites this paper.

Expert Evaluation of LLM's Open-Ended Legal Reasoning on the Japanese Bar Exam Writing Task Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T21:16:35.999751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cf8e7149-de47-4ac6-ab3d-793c264cf504 · inbound

Rethinking Evaluation for LLM Hallucination Detection: A Desiderata, A New RAG-based Benchmark, New Insights cites this paper.

Rethinking Evaluation for LLM Hallucination Detection: A Desiderata, A New RAG-based Benchmark, New Insights Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T01:37:03.592225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7b12e8c1-3462-4de6-a5bd-2529747945e7 · inbound

LegalCheck: Retrieval- and Context-Augmented Generation for Drafting Municipal Legal Advice Letters cites this paper.

LegalCheck: Retrieval- and Context-Augmented Generation for Drafting Municipal Legal Advice Letters Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:07:17.020035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9b500199-9bfd-4e79-91f2-153cfadc2c8d · inbound

LegalCheck: Retrieval- and Context-Augmented Generation for Drafting Municipal Legal Advice Letters cites this paper.

LegalCheck: Retrieval- and Context-Augmented Generation for Drafting Municipal Legal Advice Letters Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:03:47.051687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4cbf205c-8dad-4c7c-872d-56793e72a257 · inbound

ACL-Verbatim: hallucination-free question answering for research cites this paper.

ACL-Verbatim: hallucination-free question answering for research Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T04:54:35.957661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bf4c9acc-5908-45d1-8ff8-40eb0085e7b7 · inbound

Citation Grounding: Detecting and Reducing LLM Citation Hallucinations via Legal Citation Graphs cites this paper.

Citation Grounding: Detecting and Reducing LLM Citation Hallucinations via Legal Citation Graphs Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-06-28T20:32:37.526018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 99e912df-00b7-4ef5-ba2f-1e8b0ba838e4 · inbound

LLMs Prompted for Legal Context Object More: Overrefusal from Small On-Premises LLMs in Criminal Legal Context cites this paper.

LLMs Prompted for Legal Context Object More: Overrefusal from Small On-Premises LLMs in Criminal Legal Context Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T17:09:59.594322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7fe5da05-cc7b-495a-af4f-83e324d7ec9f · inbound

How Do LLMs Cite? A Mechanistic Interpretation of Attribution in Retrieval-Augmented Generation cites this paper.

How Do LLMs Cite? A Mechanistic Interpretation of Attribution in Retrieval-Augmented Generation Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T11:14:36.967248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 594e80d5-dd3f-46d7-a229-16c0088fbcc5 · inbound

Zero Hallucination, by Construction: Hallucination-Aware Layered Oversight for Trustworthy Enterprise AI cites this paper.

Zero Hallucination, by Construction: Hallucination-Aware Layered Oversight for Trustworthy Enterprise AI Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T16:45:20.138694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.