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Paper Citation Record · LEDGER

A Short Survey of Viewing Large Language Models in Legal Aspect

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2303.09136.

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

pith.paper-citation-record.v1
2303.09136 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:25:04.214978Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T23:31:11.564212Z

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 c83ce0dd-e6fc-4855-a92d-6d1bc6553411 · inbound

A Survey on Knowledge Distillation of Large Language Models cites this paper.

A Survey on Knowledge Distillation of Large Language Models A Short Survey of Viewing Large Language Models in Legal Aspect

Reference 174

Resolution
verified exact
arxiv_id, observed 2026-05-17T23:31:11.567239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-17T23:31:11.213552Z digest=sha256:a6d6f9dd783c352d8c42d37789509b0e52a20c5b661d4cfb815c9caaa3ff715a

Observation 22df3db4-ba71-469a-ac38-15feae8ce1e0 · inbound

Abstract Counterfactuals for Language Model Agents cites this paper.

Abstract Counterfactuals for Language Model Agents A Short Survey of Viewing Large Language Models in Legal Aspect

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T11:25:04.214978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:25:04.214978Z digest=sha256:41ebbc367b3f040317670426f28d3871b0dc98050b5bf246d0ba4775cfc16421

Observation caf257b6-15f8-44e9-9f62-a7f1e890266d · 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 A Short Survey of Viewing Large Language Models in Legal Aspect

Reference 177

Resolution
unresolved
no resolver link, observed 2026-08-06T18:37:11.205686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:37:11.205686Z digest=sha256:e0448f695db77d4035b0e523b836a87e1f6754ab5f8ccb7f585b13fd8553b44b

Observation 6135202b-440e-494c-9a9b-dd939697ddc2 · 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 A Short Survey of Viewing Large Language Models in Legal Aspect

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T18:22:21.226955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:22:21.226955Z digest=sha256:f3aa1e96d141371020e4bef5b6f9a3d131cb9605fad1d88b6545b13e008282c8

Observation 006a2959-ad5a-41d9-bcbe-ca5a13edc339 · inbound

Charting the Future of Scholarly Knowledge with AI: A Community Perspective cites this paper.

Charting the Future of Scholarly Knowledge with AI: A Community Perspective A Short Survey of Viewing Large Language Models in Legal Aspect

Reference 106

Resolution
unresolved
no resolver link, observed 2026-08-05T15:32:34.250377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:32:34.250377Z digest=sha256:9ceabb84be1b564ab50749d818b9d25b8ac79299f3c6f65d57ec128cd4e839e5

Observation e96bdd8e-e364-4eb7-95ea-4207c7361227 · inbound

Testing for LLM response differences: the case of a composite null consisting of semantically irrelevant query perturbations cites this paper.

Testing for LLM response differences: the case of a composite null consisting of semantically irrelevant query perturbations A Short Survey of Viewing Large Language Models in Legal Aspect

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-04T17:26:38.376545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:26:38.376545Z digest=sha256:1ea6a2abf91a798d1cd0a8aed1c02d720b660d88dbf3291da6ab5d8fb7daf16e

Observation 1aa3e1fa-b5af-4e21-ae0b-70fe5d78e96b · inbound

VLegal-Bench: Cognitively Grounded Benchmark for Vietnamese Legal Reasoning of Large Language Models cites this paper.

VLegal-Bench: Cognitively Grounded Benchmark for Vietnamese Legal Reasoning of Large Language Models A Short Survey of Viewing Large Language Models in Legal Aspect

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-16T21:38:34.201426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T21:36:24.376401Z digest=sha256:f54f708954e1e5b6097395050bb6e515c54319615ad27765dde4fb2dffae299e

Observation 15bb14fa-6fbb-4a93-9fac-d991646cb95d · inbound

VertMark: A Unified Training-Free Robust Watermarking Framework for Vertical Domain Pre-trained Language Models cites this paper.

VertMark: A Unified Training-Free Robust Watermarking Framework for Vertical Domain Pre-trained Language Models A Short Survey of Viewing Large Language Models in Legal Aspect

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T06:05:35.360539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T18:58:52.757298Z digest=sha256:eba735db0943c1233905b7b2c638d77bf47f18670d85af20a74076ec0cd29efc

Observation ef68943d-0c9f-410c-9216-d6d58eace508 · inbound

Towards Understanding Continual Factual Knowledge Acquisition of Language Models: From Theory to Algorithm cites this paper.

Towards Understanding Continual Factual Knowledge Acquisition of Language Models: From Theory to Algorithm A Short Survey of Viewing Large Language Models in Legal Aspect

Reference 106

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:56:25.534241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T04:47:54.466097Z digest=sha256:8f2f3072d3063527a8ffd9ed384101f308ba626ce368938baf0fe717c85e0c52