Paper Citation Record · LEDGER

LawBench: Benchmarking Legal Knowledge of Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 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 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:05:14.707247Z

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

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

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

Resolution: verified exact; 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 2026-08-08T06:32:00.761636+00:00.

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

Resolution: verified exact; 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 2026-08-08T06:32:00.761636+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-06T05:48:02.549792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-08T06:32:00.761636+00:00.

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

Resolution: malformed identifier; 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 2026-08-08T06:32:00.761636+00:00.

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

Resolution: malformed identifier; arxiv_id, observed 2026-06-30T17:34:57.272002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T17:09:59.606999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T13:35:49.670830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.