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Paper Citation Record · LEDGER

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models

As of 7 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 1 inbound Pith citation observation for arXiv:2506.04636.

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

pith.paper-citation-record.v1
2506.04636 v2

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:40:41.007022Z

measured 23 of 23 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T22:07:28.093248Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

22 of 22 outbound references displayed

  • verified exact0
  • verified fuzzy9
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5e160353-f0b5-4681-bc69-110d6959886c · outbound

This paper cites Open Deep Search: Democratizing Search with Open-source Reasoning Agents.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Open Deep Search: Democratizing Search with Open-source Reasoning Agents

Reference 1

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no resolver link, observed 2026-08-07T10:40:40.837757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:40:40.837757Z digest=sha256:ab0eb3d8a17e13fa24a9113e8b654af826d596c47bfed1529f43c6c2d1e70ac3

Observation a2731d44-0372-4735-a810-03c45670465c · outbound

This paper cites LEGAL-BERT: The Muppets straight out of Law School.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models LEGAL-BERT: The Muppets straight out of Law School

Reference 2

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no resolver link, observed 2026-08-07T10:40:40.896721Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T10:40:40.896721Z digest=sha256:22213cef7657d1a51d6c30e62c533104edac555696a3cff304224e854836a39b

Observation b74145d1-fafe-43e2-b6cd-39ea7436fad3 · outbound

This paper cites LexGLUE: A Benchmark Dataset for Legal Language Understanding in English.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models LexGLUE: A Benchmark Dataset for Legal Language Understanding in English

Reference 3

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no resolver link, observed 2026-08-07T10:40:40.901661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:40:40.901661Z digest=sha256:d84c9f0b69f28c0889a4cd402dd7b45aa1f1fd1d87e461c28bdac03cde111d67

Observation 6f6a8c70-596a-4679-ad27-0edec707a1b5 · outbound

This paper cites A survey on legal judgment prediction: Datasets, metrics, models and challenges.IEEE Access, 11:102050–102071, 2023.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models A survey on legal judgment prediction: Datasets, metrics, models and challenges.IEEE Access, 11:102050–102071, 2023

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-07T10:40:41.523519Z

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.

source=pdf_text observed=2026-08-07T10:40:40.907335Z digest=sha256:09354c7cda56c58a83e8216ad46b728b12845662834e98a7ce319a0dd71a2dee

Observation 8c613567-c485-44cc-9774-7af188034892 · outbound

This paper cites Victor: a dataset for brazilian legal documents classification.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Victor: a dataset for brazilian legal documents classification

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-07T10:40:41.508613Z

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.

source=pdf_text observed=2026-08-07T10:40:40.912304Z digest=sha256:40c85e86e5de32a5def11d6ebc05ba07e53903fe3846824d8494d4c37b758de9

Observation 56c9ebbc-4c97-4cb6-8efc-6bd54e4007e9 · outbound

This paper cites Corporate governance and equity prices.The quarterly journal of economics, 118(1):107–156, 2003.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Corporate governance and equity prices.The quarterly journal of economics, 118(1):107–156, 2003

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:40:41.493318Z

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.

source=pdf_text observed=2026-08-07T10:40:40.918212Z digest=sha256:f0d0356e4158f1ab36bc531d981c2ce280be32b5c9a29b9b3ed66f9eb4d32219

Observation e35098b7-fc10-4793-9953-3667d76df398 · outbound

This paper cites Ho, Christopher Ré, Adam Chilton, Aditya Narayana, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel N.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Ho, Christopher Ré, Adam Chilton, Aditya Narayana, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel N

Reference 7

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no resolver link, observed 2026-08-07T10:40:40.923860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:40:40.923860Z digest=sha256:2151fe34ba9a96ffe21023729c6b5e544e2eb749f6e7f173898c40c65c086fa9

Observation acdf0358-be33-4a82-b8c6-2c2500120456 · outbound

This paper cites Extractive summarisation of legal texts.Artificial Intelligence and Law, 14:305–345, 2006.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Extractive summarisation of legal texts.Artificial Intelligence and Law, 14:305–345, 2006

Reference 8

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raw_fallback, observed 2026-08-07T10:40:41.467016Z

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.

source=pdf_text observed=2026-08-07T10:40:40.929656Z digest=sha256:05f22dd8850961674130c511c531441bf3fac4bd469956786de7892f63eddaa1

Observation 6aa0cce1-98ca-4b72-a64c-469e4e243d98 · outbound

This paper cites CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review

Reference 9

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no resolver link, observed 2026-08-07T10:40:40.934654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:40:40.934654Z digest=sha256:6603bc6bc1b8bf2b69981bbc67c4b986c7650925342be5758799024f039403ae

Observation 80ce0ae9-14a6-40cc-96ce-783ee52ddc1d · outbound

This paper cites Text summarization from legal documents: a survey.Artificial Intelligence Review, 51:371–402, 2019.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Text summarization from legal documents: a survey.Artificial Intelligence Review, 51:371–402, 2019

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-07T10:40:41.452154Z

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.

source=pdf_text observed=2026-08-07T10:40:40.941016Z digest=sha256:89b342d2dea5dfca1827c351204b43b19e7b5e05e354f86786dce12a5b8fa1d2

Observation c9a5d10c-4c7d-4dd6-b221-baa3ff259833 · outbound

This paper cites ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts

Reference 11

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no resolver link, observed 2026-08-07T10:40:40.946540Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T10:40:40.946540Z digest=sha256:eff63fddc86d9dc466551810dc1b558de109bee4d328f91d7408f19d1113ef22

Observation a3794354-b891-40e5-9e0d-9d50eeb0316f · outbound

This paper cites Chain of Code: Reasoning with a Language Model-Augmented Code Emulator.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Chain of Code: Reasoning with a Language Model-Augmented Code Emulator

Reference 12

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no resolver link, observed 2026-08-07T10:40:40.952752Z

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source=pdf_text observed=2026-08-07T10:40:40.952752Z digest=sha256:59ce0992453023b888227e743ebc97dc69aeb891fad35da00542a9e008826440

Observation 37ad03d0-8809-4949-a73f-3dfa13dcb3f8 · outbound

This paper cites Lecard: a legal case retrieval dataset for chinese law system.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Lecard: a legal case retrieval dataset for chinese law system

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:40:41.436816Z

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.

source=pdf_text observed=2026-08-07T10:40:40.958351Z digest=sha256:5779bc564d4306ef86cfc8dcfd5811e9220f1d2d2b90d052450da2b72dcc83f1

Observation 9ed7526a-1c8c-417b-9f37-6c084cee3f0d · outbound

This paper cites Legal natural language processing from 2015 to 2022: A comprehensive systematic mapping study of advances and applications.IEEE Access, 12: 145286–145317, 2024.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Legal natural language processing from 2015 to 2022: A comprehensive systematic mapping study of advances and applications.IEEE Access, 12: 145286–145317, 2024

Reference 14

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raw_fallback, observed 2026-08-07T10:40:41.228666Z

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.

source=pdf_text observed=2026-08-07T10:40:40.963985Z digest=sha256:a9a8c2074f5d8f3a25482a3611ea186c94d536e54a1b9211d9ba184b6ef7b4d1

Observation ef1f762d-33d9-4cc2-91a7-de3ad4ff2a69 · outbound

This paper cites Large Scale Legal Text Classification Using Transformer Models.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Large Scale Legal Text Classification Using Transformer Models

Reference 15

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source=pdf_text observed=2026-08-07T10:40:40.969103Z digest=sha256:53f9aeeea20aba5c153211316a371e240368c1d10681a458e74d19f5c9341646

Observation 5f9fddc1-1fb0-4db3-8f2a-fa1ee4fd5993 · outbound

This paper cites A comparative study of classifying legal documents with neural networks.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models A comparative study of classifying legal documents with neural networks

Reference 16

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raw_fallback, observed 2026-08-07T10:40:41.399416Z

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.

source=pdf_text observed=2026-08-07T10:40:40.974749Z digest=sha256:6edeb91ff731755a51d39cb5cee881c1dacb95586ba9fba700e6babe78a9e7ef

Observation c6fc253e-32d6-4708-9587-562c8f1a3878 · outbound

This paper cites Long-length Legal Document Classification.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Long-length Legal Document Classification

Reference 17

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no resolver link, observed 2026-08-07T10:40:40.979925Z

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source=pdf_text observed=2026-08-07T10:40:40.979925Z digest=sha256:5a5ba66ac6bf2726fd7554f28ca1948b500062cb1471a0b8984af27d5eb3b5c5

Observation c57ccd84-97fc-4983-ad07-b6df1627702d · outbound

This paper cites MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding

Reference 18

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source=pdf_text observed=2026-08-07T10:40:40.985380Z digest=sha256:5520b5ad95a39ea996595f65dcb1be004aba50da1874372ac1ab6e9a7f84bcaf

Observation 76d20f26-98b0-4d99-b170-c03578071a78 · outbound

This paper cites Empirical study of deep learning for text classification in legal document review.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Empirical study of deep learning for text classification in legal document review

Reference 19

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raw_fallback, observed 2026-08-07T10:40:41.380565Z

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.

source=pdf_text observed=2026-08-07T10:40:40.990384Z digest=sha256:046499395330d574f04f573c5e390e46d69333e6eb14576633ad3a826498c3ca

Observation 7af34551-f46f-4e50-ba2a-7bf81b0575a2 · outbound

This paper cites CAIL2018: A Large-Scale Legal Dataset for Judgment Prediction.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models CAIL2018: A Large-Scale Legal Dataset for Judgment Prediction

Reference 20

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source=pdf_text observed=2026-08-07T10:40:40.995362Z digest=sha256:d45d577336369d10d5c4be9041736cca3ba3e53efa49aa7437c049469f693671

Observation 2135f05e-8ab2-4c12-bf86-00d001aec977 · outbound

This paper cites React: Synergizing reasoning and acting in language models.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models React: Synergizing reasoning and acting in language models

Reference 21

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source=pdf_text observed=2026-08-07T10:40:41.000660Z digest=sha256:11109daf08deb3b2782f83f66a163f7199cc9ff346486703671aa2dfcbd4fafd

Observation 319832f5-404a-486a-b0c9-186b5edddfb9 · outbound

This paper cites Delaware courts have consistently held.

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models Delaware courts have consistently held

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-07T10:40:41.352774Z

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.

source=pdf_text observed=2026-08-07T10:40:41.007022Z digest=sha256:5ea7c6ef37e2621502f34f928232da7e7786879509a86c40d4be69339c0bd697

Pith citing papers

Observation 591a75ad-c162-4a0d-ac80-0c204259a67b · inbound

DECODEM: Data Extraction from Corporate Organizational Documents via Enhanced Methods cites this paper.

DECODEM: Data Extraction from Corporate Organizational Documents via Enhanced Methods CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models

Reference 2025

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no resolver link, observed 2026-08-01T22:07:28.093248Z

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source=pdf_text observed=2026-08-01T22:07:28.093248Z digest=sha256:ae079ac643e6a45173e62c9e47e8effc4c9550e860eb8e108fc50d5236808d06