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Paper Citation Record · LEDGER

LawBench: Benchmarking Legal Knowledge of Large Language Models

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:2309.16289.

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

pith.paper-citation-record.v1
2309.16289 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:17:09.758834Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:09:59.605615Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3b8455b4-e4d3-43fa-896b-5433f6d9ea09 · inbound

TrustLLM: Trustworthiness in Large Language Models cites this paper.

TrustLLM: Trustworthiness in Large Language Models LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 120

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arxiv_id, observed 2026-05-18T11:17:08.510629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-18T11:17:08.108565Z digest=sha256:4f0b0e7bcb348eb9b6ec3ea5d78760c42e92b987298ed86d43f13716d87fc377

Observation 02d736b2-9957-4098-9ef1-eb5ab78c9a94 · inbound

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models cites this paper.

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 142

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arxiv_id, observed 2026-05-13T13:43:11.203691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-13T13:43:11.024069Z digest=sha256:db0eb99b79f0a2e97c0843c3bdb8c86471602ca1bd3274e2eb7959b2e846bb30

Observation 5598b24a-5f24-4db7-b9d1-0aac9c19e54f · inbound

QA-TOOLBOX: Conversational Question-Answering for process task guidance in manufacturing cites this paper.

QA-TOOLBOX: Conversational Question-Answering for process task guidance in manufacturing LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 18

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no resolver link, observed 2026-08-11T23:17:09.758834Z

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source=pdf_text observed=2026-08-11T23:17:09.758834Z digest=sha256:c4e9119ddece1d21694d7057f3472ecbf1106482f4bd116fe9dc479e72e1cc56

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

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

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

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source=arxiv_source observed=2026-08-11T19:55:13.971200Z digest=sha256:7a5efdb81260a1667f17f931a5c739192dc096de12d1892ad0fc3eff90cac13c

Observation 72aada3b-898c-40ff-aaac-12be985d4f92 · inbound

CitaLaw: Enhancing LLM with Citations in Legal Domain cites this paper.

CitaLaw: Enhancing LLM with Citations in Legal Domain LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 4

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no resolver link, observed 2026-08-11T12:10:16.843139Z

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source=pdf_text observed=2026-08-11T12:10:16.843139Z digest=sha256:a3371d401d13dd91da0f9a36ce37417a2ef5fca9d588b7a22ddf6cb71744595b

Observation b35aeeb3-ff46-435a-8d71-10af2dc4939d · inbound

Beyond Guilt: Legal Judgment Prediction with Trichotomous Reasoning cites this paper.

Beyond Guilt: Legal Judgment Prediction with Trichotomous Reasoning LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 12

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no resolver link, observed 2026-08-11T12:10:00.543684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:10:00.543684Z digest=sha256:f48976b583b35db15576129e519510480128c2f67a7f91563602f98ac9f219e3

Observation 5dba7655-5211-4b36-9efb-048dd8853534 · inbound

PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation cites this paper.

PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 23

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no resolver link, observed 2026-08-10T18:13:08.509992Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T18:13:08.509992Z digest=sha256:c22f4bdcbcf03605c0e84543af7571b3dca3ee88199ddcf55b592d532d7fe171

Observation 87d62a63-1f29-46f3-b3fd-46e0a97eeaa3 · inbound

Improving LLM Leaderboards with Psychometrical Methodology cites this paper.

Improving LLM Leaderboards with Psychometrical Methodology LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 25

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no resolver link, observed 2026-08-10T12:49:36.919546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T12:49:36.919546Z digest=sha256:50bcb5e62debb2d387d13eeed184ad635f5303d4ae0174e2aa77c2c3bfd8d239

Observation ae31c3ca-d2a7-4e4e-afd9-16a687513e3c · inbound

Artificial Intelligence and Legal Analysis: Implications for Legal Education and the Profession cites this paper.

Artificial Intelligence and Legal Analysis: Implications for Legal Education and the Profession LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 5

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no resolver link, observed 2026-08-09T11:30:13.556135Z

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source=pdf_text observed=2026-08-09T11:30:13.556135Z digest=sha256:5363c4dfde0df6e0e4cc4f324833f15ae64d8ecd74f66d06822c88d8bff957b9

Observation 0f3e0843-d7b5-4c9d-9ed0-4a1139238e38 · inbound

LawGPT: Knowledge-Guided Data Generation and Its Application to Legal LLM cites this paper.

LawGPT: Knowledge-Guided Data Generation and Its Application to Legal LLM LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 2022

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no resolver link, observed 2026-08-08T15:05:14.707247Z

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source=pdf_text observed=2026-08-08T15:05:14.707247Z digest=sha256:3cf32c44dcf9106648949477ff1f1ba5244f32149b87ab2e109e57d643dd75f8

Observation 27fb1375-bff2-4cba-a340-09b8db6da751 · inbound

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning cites this paper.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 17

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no resolver link, observed 2026-08-07T15:37:26.187600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:37:26.187600Z digest=sha256:27e29a7cd09d166516bbcbcc70eb96d464bbcfcba7d41aba363afc9ce132f146

Observation 4293e07d-6ce2-4233-943b-9a948726d8b8 · inbound

Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition cites this paper.

Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 8

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no resolver link, observed 2026-08-07T13:16:12.976983Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:16:12.976983Z digest=sha256:38790215f79589e9e292012dc10138561b0bdbd609e2860cc6e51574d866c0e2

Observation d7d01fe2-569a-482f-abd2-30009e91163c · inbound

Measuring Faithfulness and Abstention: An Automated Pipeline for Evaluating LLM-Generated 3-ply Case-Based Legal Arguments cites this paper.

Measuring Faithfulness and Abstention: An Automated Pipeline for Evaluating LLM-Generated 3-ply Case-Based Legal Arguments LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 10

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no resolver link, observed 2026-08-07T12:03:18.771662Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:03:18.771662Z digest=sha256:ea5aa49d9d3be47b24c93dd90f818af7de91f44e53d89956afe5e97d5e643aa5

Observation fa7038fa-4849-4b6f-8f9b-52045e7bc1d0 · inbound

A Survey of Automatic Evaluation Methods on Text, Visual and Speech Generations cites this paper.

A Survey of Automatic Evaluation Methods on Text, Visual and Speech Generations LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 66

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no resolver link, observed 2026-08-07T10:17:46.451524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:17:46.451524Z digest=sha256:d45acfb7a241ffde87871ca02251958d497b623261b8dce5640fbc5d30640475

Observation 7761a91c-d7ac-4b84-97c6-a01601180a10 · inbound

ASP2LJ : An Adversarial Self-Play Laywer Augmented Legal Judgment Framework cites this paper.

ASP2LJ : An Adversarial Self-Play Laywer Augmented Legal Judgment Framework LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 13

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no resolver link, observed 2026-08-07T04:54:25.711725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:54:25.711725Z digest=sha256:27d6c8940d806882fb9c5bc27111d5b5371150ccb4926d059c2577b0b5a8d7e4

Observation 22779890-ffe0-482e-977c-a20e2120b210 · inbound

Enterprise Large Language Model Evaluation Benchmark cites this paper.

Enterprise Large Language Model Evaluation Benchmark LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 22

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no resolver link, observed 2026-08-06T22:56:32.291657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:56:32.291657Z digest=sha256:6b26fa6c16f1d0057b539829a49da492619f4d913080861f39c683212a6a3db3

Observation ccdfe17c-d3bd-4f87-b379-cdbef44069de · inbound

When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance cites this paper.

When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 56

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no resolver link, observed 2026-08-06T18:37:08.052994Z

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source=pdf_text observed=2026-08-06T18:37:08.052994Z digest=sha256:7ec3f4a30ae62f3599e4ca097e9bb96fcfaf5ce4d12767a325c3877c5bb4eb29

Observation ec4f2b42-a63e-41b2-8fce-2a5e4192f98e · inbound

Using Large Language Models for Legal Decision-Making in Austrian Value-Added Tax Law: An Experimental Study cites this paper.

Using Large Language Models for Legal Decision-Making in Austrian Value-Added Tax Law: An Experimental Study LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 9

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no resolver link, observed 2026-08-06T18:22:21.201277Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:22:21.201277Z digest=sha256:e4b71579416f6418244751afb6599d8907360342a2a9fae29d1667c534942246

Observation a5bd44a8-2f20-4a47-80a5-fa635c0e9631 · inbound

Towards Evaluation for Real-World LLM Unlearning cites this paper.

Towards Evaluation for Real-World LLM Unlearning LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 6

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:48:02.549792Z digest=sha256:1c1d47096936f082293e5e2dea79093256bd3e3c5a3293ec2ed48151581fb9ed

Observation b8d62879-b338-4504-8847-4674ceb95bab · 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 LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 9

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no resolver link, observed 2026-08-05T15:51:46.259386Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:51:46.259386Z digest=sha256:55a7b8fcaf322cfd5caaa56aa95bb1712155d108bbdfed6a61e66763627f58cc

Observation 73607cfe-56a0-4dad-bcf7-da49325fa311 · inbound

Benchmarking LLM-Assisted Blue Teaming via Standardized Threat Hunting cites this paper.

Benchmarking LLM-Assisted Blue Teaming via Standardized Threat Hunting LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 10

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no resolver link, observed 2026-08-04T14:42:56.728972Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:42:56.728972Z digest=sha256:8261e1bd0d6ca2f64bb27b196fd17be34758cf3376f59b28e840fba4a67d7061

Observation 62894b9d-fdde-41ec-9459-1ae0ce80b515 · inbound

MinT: Managed Infrastructure for Training and Serving Millions of LLMs cites this paper.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 5

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verified exact
arxiv_id, observed 2026-05-14T19:27:51.803748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-14T19:25:12.407148Z digest=sha256:58f0b81e592fe829fa3ae510c66248b77363bc72454fe8ae2f078637eeeee08c

Observation b427aebe-8038-408e-9ace-722d433a6351 · inbound

MinT: Managed Infrastructure for Training and Serving Millions of LLMs cites this paper.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 5

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verified exact
arxiv_id, observed 2026-06-30T22:05:06.267674Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-30T21:47:00.295144Z digest=sha256:c215459b7ae2a5c3dc4ac158d40db709cd3e4a3dee38ecaf55544228dceb34f4

Observation b9d7fa77-f733-4b31-83ee-228b155f0fc6 · inbound

Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements cites this paper.

Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 7

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arxiv_id, observed 2026-05-22T06:54:42.132862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-22T06:52:20.455300Z digest=sha256:4e417ce0b4bffe83fcc574d1c65ace1b99d642f383aa06b64d4b86f81a9806ab

Observation 33e67669-e537-4f61-b40a-2e78729a8591 · inbound

Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements cites this paper.

Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 7

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arxiv_id, observed 2026-06-30T17:34:57.272002Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-30T17:34:52.256466Z digest=sha256:c39841747c24ac7620488ee610a77b78c690f5841936510c79de0c249bb447cb

Observation 4496cb5e-89da-484a-b6d7-7019ec35e17a · 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 LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 4

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arxiv_id, observed 2026-07-04T17:09:59.606999Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-25T23:51:35.265525Z digest=sha256:df815824222a217a55ac284ba2847e2aa8724bc1c5dd0711836dd70228250c81

Observation 565ac062-1a69-4c47-90a9-418e1c37b090 · inbound

What out-of-the-box LLMs can(t) do in law? A Turing test in Italian exams for lawyers, judges and notaries cites this paper.

What out-of-the-box LLMs can(t) do in law? A Turing test in Italian exams for lawyers, judges and notaries LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 2024

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:35:49.670830Z digest=sha256:79d7521aad126ed216e949de3645c9f0fea8ed57a0cf0875d4a609a54107dd4c