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Paper Citation Record · LEDGER

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents

As of 8 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2608.06312.

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

pith.paper-citation-record.v1
2608.06312 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:49:29.665310Z

measured 61 of 61 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

61 of 61 outbound references displayed

  • verified exact1
  • verified fuzzy20
  • unresolved38
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b37b6b9a-8584-4f6c-a980-a15d897d638e · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 1

Resolution
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no resolver link, observed 2026-08-07T05:49:21.426003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:21.426003Z digest=sha256:e14e7858e03903a35cc6fe2110b1ffe5c2be16dcec11009b47af9a3171462c75

Observation bd19dba9-daab-4af5-a676-27a0c8874d44 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2

Resolution
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no resolver link, observed 2026-08-07T05:49:21.587773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:21.587773Z digest=sha256:bee410f020e7979140b7e8bc019a2c65da8e4ac2de2babd73b985c63b542f799

Observation 92fb491b-8fd4-4a51-979f-0f82a19fcf67 · outbound

This paper cites Qwen2.5-1M Technical Report.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Qwen2.5-1M Technical Report

Reference 3

Resolution
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no resolver link, observed 2026-08-07T05:49:21.792007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:21.792007Z digest=sha256:307ad64b6f60b32df459640d96c6239d1d545722ec2532cbfc2207bf008e39c4

Observation 8284316d-0863-44f2-82db-9e83188366f6 · outbound

This paper cites The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:21.906429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:21.906429Z digest=sha256:49e59a00d0b8eb01b802114428325885ad77e2ad1ebc69558c11db24fe98c682

Observation 80cfdfbf-6077-431e-874c-c387e22c91dd · outbound

This paper cites arXiv preprint arXiv:2606.19348 , year=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents arXiv preprint arXiv:2606.19348 , year=

Reference 5

Resolution
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no resolver link, observed 2026-08-07T05:49:22.042799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:22.042799Z digest=sha256:b9e9cc87eface3a56bdda601167f21da417882c2462b738736eb4c19bf712a6d

Observation 59b0843f-8750-4016-b0e9-f8640e2261d6 · outbound

This paper cites Qwen3 Technical Report.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Qwen3 Technical Report

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:22.171137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:22.171137Z digest=sha256:58d21a0224e4195c0e4ca21f6c60f068d500b8503d38e116743452e216cf0c02

Observation b630b7ca-6ffc-431b-9edd-fdf5e481aca6 · outbound

This paper cites Advances in neural information processing systems , volume=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Advances in neural information processing systems , volume=

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:22.297590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:22.297590Z digest=sha256:07c41a10b4091257d366ac19c60203f3753ec0514519c0f8d735dd0bb6d55fe4

Observation c4a4b59a-ac4d-4c09-a082-7f7bea8394e3 · outbound

This paper cites Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:36.529940Z

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.

source=arxiv_source observed=2026-08-07T05:49:22.419479Z digest=sha256:07f17af8c8575782c5ba876d93716fe9804c6edcf4cb747850ec0c19f830d1a0

Observation 3c174370-f9db-4992-871d-6e304f3ff8f6 · outbound

This paper cites Proceedings of the 2024 conference on empirical methods in natural language processing , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the 2024 conference on empirical methods in natural language processing , pages=

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:22.477170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:22.477170Z digest=sha256:f6599dc9f096d141f83cc5a6d410ea2d34f0f6e47c5fe9785989a792d85f1ae7

Observation 9aba8d10-e3a3-4def-9019-6400ed2ab84d · outbound

This paper cites an unresolved cited work.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Unresolved cited work

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:22.599267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:22.599267Z digest=sha256:3deb2096ba2f3427203a4ca680b591797f321f27bf0f84da3c0f6d52ae0f882c

Observation 2fdf6f0f-c378-45cf-864d-ec74793a0c1b · outbound

This paper cites FinanceBench: A New Benchmark for Financial Question Answering.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents FinanceBench: A New Benchmark for Financial Question Answering

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:22.717449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:22.717449Z digest=sha256:6334ff58e1ab7ba252a198c0e87ee8895e18e6fecce6799d30f70836ebde2358

Observation 47f26a0f-fd5e-4fb8-89c7-209bae63279e · outbound

This paper cites Advances in neural information processing systems , volume=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Advances in neural information processing systems , volume=

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:36.221633Z

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.

source=arxiv_source observed=2026-08-07T05:49:22.839136Z digest=sha256:7a00871d3908314fa6c081026cd0bd5dc1dfd7ce358a66fd33081681ce6276ee

Observation a2cbf0e8-2070-49ed-9a0e-518ab9390502 · outbound

This paper cites an unresolved cited work.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:49:36.086564Z

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.

source=arxiv_source observed=2026-08-07T05:49:22.990288Z digest=sha256:d296dd46bf210c39343777372f63d71ab7c1b770cac1f9b4ebf0b1972171980a

Observation 1f3d1138-35dc-4b92-ae7d-067bca1052a1 · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL 2024 , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Findings of the Association for Computational Linguistics: ACL 2024 , pages=

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:35.848745Z

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.

source=arxiv_source observed=2026-08-07T05:49:23.110667Z digest=sha256:f93b1cdf77acf000c555ae6063b935139f2fd21e113f15d37ddab33f31cae382

Observation b98f823e-a5c1-410b-a8ed-15b414286bd2 · outbound

This paper cites Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) , pages=

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:35.657836Z

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.

source=arxiv_source observed=2026-08-07T05:49:23.254352Z digest=sha256:20660832de7bc508369b392412c7674e1d362681da642e862ead43a1342256c1

Observation 41b49ea8-bfa2-48d4-abef-ea158fbca7c5 · outbound

This paper cites Journal of Artificial Intelligence Research , author=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Journal of Artificial Intelligence Research , author=

Reference 16

Resolution
metadata mismatch
raw_fallback, observed 2026-08-07T05:49:31.002254Z

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.

source=arxiv_source observed=2026-08-07T05:49:23.304807Z digest=sha256:20349cb14efa7415fa01daea84fe5789316b65012c3e958039ee79bdd4ac3175

Observation 4ec7759e-b5f4-45c8-b190-84700ff4e436 · outbound

This paper cites MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:23.473812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:23.473812Z digest=sha256:9240a377778105263f25b2a5b1d9288be569d5bb60bb0ff57ac50a7e6632b186

Observation 3d5afadd-873b-45c2-9a3f-c8c228fae72c · outbound

This paper cites The Eleventh International Conference on Learning Representations , year=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents The Eleventh International Conference on Learning Representations , year=

Reference 18

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unresolved
no resolver link, observed 2026-08-07T05:49:23.580799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:23.580799Z digest=sha256:04d3bab671c2060a8bc1e44e883c275389a5cb6eaed6e4893733b8974c63093e

Observation 466d58f9-4e69-4b7c-8028-ba8840fdb24f · outbound

This paper cites Advances in neural information processing systems , volume=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Advances in neural information processing systems , volume=

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:23.681253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:23.681253Z digest=sha256:3eb1736d1bc0c9349f53f14baf255bdaeda35eedc8f26e039abcf74eaa05954e

Observation 87782e9f-23b8-446e-a42f-fe0afb16d460 · outbound

This paper cites Gorilla: Large Language Model Connected with Massive APIs.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Gorilla: Large Language Model Connected with Massive APIs

Reference 20

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no resolver link, observed 2026-08-07T05:49:23.853606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:23.853606Z digest=sha256:5557dd8f97ea40289c6693106b5f4072681b99c0f1a96672c6b45d56d461789a

Observation 96ccf7ed-6252-41c9-8e5d-24e4c0350a08 · outbound

This paper cites International Conference on Learning Representations , volume=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents International Conference on Learning Representations , volume=

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:23.957081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:23.957081Z digest=sha256:7178250523909f78d711093404c15f62ff7c081a36ffa2e31b1fc0f16ea1415b

Observation 35f5cad1-29da-44c4-8384-2a8dd1edc1f0 · outbound

This paper cites AutoGen: Enabling Next-Gen.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents AutoGen: Enabling Next-Gen

Reference 22

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no resolver link, observed 2026-08-07T05:49:24.101295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:24.101295Z digest=sha256:2ac3424a50f01892c1717ac684c93a8506eb6d8b1542873c7b360da1566ce7d9

Observation 2d4f6248-2e21-4611-9e32-a56ce8cda2ff · outbound

This paper cites TaskWeaver: A Code-First Agent Framework.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents TaskWeaver: A Code-First Agent Framework

Reference 23

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no resolver link, observed 2026-08-07T05:49:24.214318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:24.214318Z digest=sha256:b0621132bb7b95c9896f936dfe75e28bb70b47133c2d298b8e944802e0b28ad7

Observation c35b6044-3b53-4072-99e0-ade721890492 · outbound

This paper cites International Conference on Learning Representations , volume=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents International Conference on Learning Representations , volume=

Reference 24

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no resolver link, observed 2026-08-07T05:49:24.354531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:24.354531Z digest=sha256:6bb75bba447b7e6712fb9d96a7a4c7bb56c2c75155cbf481bd9c05e5ff91f3f4

Observation 703149a1-8c74-40fc-a9a4-db07354d1a1c · outbound

This paper cites 27th USENIX Security Symposium (USENIX Security 18) , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents 27th USENIX Security Symposium (USENIX Security 18) , pages=

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:35.359609Z

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.

source=arxiv_source observed=2026-08-07T05:49:24.496458Z digest=sha256:2ecd6878e04df4ca91b799404108ba60075d48dd24c216a05ee9add8f1dee074

Observation 52a455d7-b3e0-4f7d-819e-f1bac2772824 · outbound

This paper cites an unresolved cited work.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:49:35.129594Z

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.

source=arxiv_source observed=2026-08-07T05:49:24.617899Z digest=sha256:e101f30d02e7bff91047b2937318f956c4a12a789fca0ec76b7d605de10393c2

Observation 979ee601-0b57-4618-a153-621512fefc75 · outbound

This paper cites Findings of the Association for Computational Linguistics: EMNLP 2020 , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Findings of the Association for Computational Linguistics: EMNLP 2020 , pages=

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:34.889133Z

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.

source=arxiv_source observed=2026-08-07T05:49:24.754758Z digest=sha256:a52316afffb4279dc9e25a6a43217ae9aa45528f9eb47fad9e419003e424214f

Observation f60bf87b-bb7e-405d-a00e-09e3aa494843 · outbound

This paper cites IEEE Transactions on Software Engineering , volume=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents IEEE Transactions on Software Engineering , volume=

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:34.597353Z

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.

source=arxiv_source observed=2026-08-07T05:49:24.875193Z digest=sha256:763b6957b69ecdd443d73b9e6c60692bf571b376678b156d6475fcb75a43048f

Observation 4733c1ea-477e-4983-86d6-43eaf372d376 · outbound

This paper cites ACM Computing Surveys (CSUR) , volume=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents ACM Computing Surveys (CSUR) , volume=

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:34.347062Z

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.

source=arxiv_source observed=2026-08-07T05:49:25.025546Z digest=sha256:1c9a64c5deb2649ec5f1d3dd5de12ec6c4e3536a9d5419869e3c43bd192c01e7

Observation 1cd4c3b9-b3a1-48ea-9307-d402208c8433 · outbound

This paper cites txt, a cheap Shallow Parsing approach for Regulatory texts , author=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents txt, a cheap Shallow Parsing approach for Regulatory texts , author=

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-07T05:49:34.120058Z

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.

source=arxiv_source observed=2026-08-07T05:49:25.122241Z digest=sha256:0983bd63ae30309f679e3aff059b31778ba2b373d382204edd49e4b52dd17f16

Observation 51c5e303-25ce-4e2d-bb93-ae9122af5925 · outbound

This paper cites Scientific data , volume=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Scientific data , volume=

Reference 31

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unresolved
no resolver link, observed 2026-08-07T05:49:25.284368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:25.284368Z digest=sha256:86a1d397e303bdc0d1a93adbc4a7392574faccc7785ef3c113135abc4b49dbab

Observation f4c3eb73-51d7-4ea9-a357-82a34af1f394 · outbound

This paper cites arXiv preprint arXiv:2603.23519 , year=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents arXiv preprint arXiv:2603.23519 , year=

Reference 32

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unresolved
no resolver link, observed 2026-08-07T05:49:25.427561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:25.427561Z digest=sha256:9a9a3068defce2e7ece2887352a6a745693de24136c55a695d14fbba0b2748fd

Observation ef29c3c1-c174-4a35-82f4-bdaa05fa2d07 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:33.951222Z

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.

source=arxiv_source observed=2026-08-07T05:49:25.598133Z digest=sha256:06673d0a447401fbfc7bff55a8397ff3fe7fa65ffed75b83c8fb8b6b1f25a884

Observation 512d389f-089d-4e7f-87fe-b24af1f95f30 · outbound

This paper cites IEEE access , volume=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents IEEE access , volume=

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:33.699240Z

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.

source=arxiv_source observed=2026-08-07T05:49:25.730365Z digest=sha256:59e793ec151151b80baaec86c7de06196a40cbcfd6f1317dfd6e338b662bf460

Observation a4c44893-cfa7-4c47-baba-d55b18892a61 · outbound

This paper cites Proceedings of the 62nd annual meeting of the association for computational linguistics (volume 1: Long papers) , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the 62nd annual meeting of the association for computational linguistics (volume 1: Long papers) , pages=

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:25.883922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:25.883922Z digest=sha256:eff7ad9ce8ea0865809cd317920faabb1d25bbb5ebf2a7542912a9cb65d158d5

Observation a012409d-df1a-40f6-ad11-7264d22f3202 · outbound

This paper cites Qwen-Image Technical Report.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Qwen-Image Technical Report

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:26.030021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:26.030021Z digest=sha256:581119df35acfe68d3ffe473a7cfe32039b718acb6f021311f3473bf7ee1084e

Observation de703f0b-4940-4d19-abe1-5f57d4f70b4a · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:33.471774Z

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.

source=arxiv_source observed=2026-08-07T05:49:26.100249Z digest=sha256:4675dd74a75228cbc0b22cfbd99843c15320e1ef34992b6fcdced43206497d03

Observation ffa1beb4-6f22-4071-bb82-b6c6eb196cbe · outbound

This paper cites IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:26.272401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:26.272401Z digest=sha256:741d813a7995b07081302c2a410e124e2340d47151a6c517e9dced462dde41ed

Observation 02b65240-d639-49a1-9b42-c69f69d3c874 · outbound

This paper cites Physical-Layer Signal Injection Attacks on EV Charging Ports: Bypassing Authentication via Electrical-Level Exploits.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Physical-Layer Signal Injection Attacks on EV Charging Ports: Bypassing Authentication via Electrical-Level Exploits

Reference 39

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T05:49:30.511176Z

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.

source=arxiv_source observed=2026-08-07T05:49:26.400199Z digest=sha256:3405892c94826fbc591f34cfbdcc62d56bfe2e630b7b5f6d3ab6b16a368ed5ba

Observation 242de829-b719-45be-9f7b-b5082b603965 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models , url =.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Chain-of-Thought Prompting Elicits Reasoning in Large Language Models , url =

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:26.504189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:26.504189Z digest=sha256:b6dff59ea8d8989283bb862fd4022e72daa8c555fe5e2ba7a5c0b57c0ce35ebc

Observation f172a2cf-2dfc-4a2e-957d-28faa14bc159 · outbound

This paper cites The Eleventh International Conference on Learning Representations , year=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents The Eleventh International Conference on Learning Representations , year=

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:26.642090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:26.642090Z digest=sha256:757db739ec3500e4e23c3e606a25e3bde29c3465dd9929d17c9ca1a3072f67ad

Observation 306b460d-25b3-497c-8070-96873e6f248c · outbound

This paper cites Training language models to follow instructions with human feedback , url =.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Training language models to follow instructions with human feedback , url =

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:26.760835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:26.760835Z digest=sha256:c98d128750d45c09f90d76b0c22ed274b10ab9062ff9e29c66371f41f3aa05f0

Observation c2ea905e-d121-4c2c-a2ed-9093b0fef070 · outbound

This paper cites L -Eval: Instituting Standardized Evaluation for Long Context Language Models.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents L -Eval: Instituting Standardized Evaluation for Long Context Language Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:26.887268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:26.887268Z digest=sha256:219d3e750fc8163f9ab4cddf3e9466238c9d0cbc160d8e79191f146bf7f2c1ae

Observation a2893ee0-873e-4f2c-b6df-5752ca009e71 · outbound

This paper cites 2024 , url=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents 2024 , url=

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:27.036670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:27.036670Z digest=sha256:f820572eb9c8147f51f7cd2935720a47d831ab4d076b341900bd468f2f92b92f

Observation 795929a7-6e76-4f86-815b-62c60dbc1b66 · outbound

This paper cites Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:33.247361Z

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.

source=arxiv_source observed=2026-08-07T05:49:27.219944Z digest=sha256:03fb61af31137e865dd62fc41f745b89085cb957881be6750dd78251dc9c13a0

Observation ecbbfaf4-7382-4eb5-81d4-a6e294d8bce3 · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents The Twelfth International Conference on Learning Representations , year=

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:33.005112Z

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.

source=arxiv_source observed=2026-08-07T05:49:27.346997Z digest=sha256:e74b0cbf064b709b77c0c8f73ffb7e79a4b921a89381799a0ba15f01809e3036

Observation 1e5fe0e4-6e43-4227-b72b-a17bcc82f408 · outbound

This paper cites Findings of the Association for Computational Linguistics: EMNLP 2021 , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Findings of the Association for Computational Linguistics: EMNLP 2021 , pages=

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:27.481197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:27.481197Z digest=sha256:890d905804f8b5b702f333286d2345a8aa2f1c46dc9f675d04c8398d4f162598

Observation 75141fb6-23de-496d-b27d-44c0aca8683c · outbound

This paper cites and Gardner, Matt.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents and Gardner, Matt

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:27.653428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:27.653428Z digest=sha256:e999d6f69cd3a2e2dffacff7bfaaa14864bb859055b5e1f7c473412f1f0dde01

Observation 86bd0a3c-775e-4888-a8d5-af4b227376b3 · outbound

This paper cites ACORD : An Expert-Annotated Retrieval Dataset for Legal Contract Drafting.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents ACORD : An Expert-Annotated Retrieval Dataset for Legal Contract Drafting

Reference 49

Resolution
verified exact
doi, observed 2026-08-07T05:49:29.986176Z

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.

source=arxiv_source observed=2026-08-07T05:49:27.790026Z digest=sha256:a433d88469ca9989e36092532e4b4bb219c72a287098c27472c65f3b5cc59070

Observation 8aad16ee-e78a-471b-bc75-66c812633682 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Advances in Neural Information Processing Systems , volume=

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:32.785964Z

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.

source=arxiv_source observed=2026-08-07T05:49:27.921356Z digest=sha256:7ea30fdcc90705acb1944c3a6721fc9b5a5f7f4421eb1ae71d3efb2e2aa8a69a

Observation 095c4c7f-a0a6-4fcd-9c84-9a6d94da84a5 · outbound

This paper cites Proceedings of the 2018 conference of the North American chapter of the Association for Computational Linguistics: Human language technologies, volume 1 (long papers) , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the 2018 conference of the North American chapter of the Association for Computational Linguistics: Human language technologies, volume 1 (long papers) , pages=

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:32.553618Z

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.

source=arxiv_source observed=2026-08-07T05:49:28.063746Z digest=sha256:cd54620591316bc2e8488615fb74990c5bdb5874d5a402f617fe6b5b11887f0f

Observation ae454bf9-16be-4ff2-80f4-b9f093308b00 · outbound

This paper cites Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:32.276411Z

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.

source=arxiv_source observed=2026-08-07T05:49:28.241869Z digest=sha256:9bff1209b038bac413aae28c9b3db095ff176abd6018c4cef14204f4cfb25d0f

Observation f0984ac8-6f3f-444b-923d-4ccaf755acbf · outbound

This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:28.453015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:28.453015Z digest=sha256:d2b38029605808bd82e7ae13f045147210056bcfed1bc3a9628b8d25774d4d73

Observation 8774cbed-a1af-4790-aeb9-6cb58f71064d · outbound

This paper cites D oc M ath-Eval: Evaluating Math Reasoning Capabilities of LLM s in Understanding Long and Specialized Documents.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents D oc M ath-Eval: Evaluating Math Reasoning Capabilities of LLM s in Understanding Long and Specialized Documents

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:28.624966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:28.624966Z digest=sha256:83752f14036f4d98b249de78af213f61576121f7a576e2031c1750d61e0d6629

Observation ef2ffef8-dae6-4c41-abe8-7f38a7643daa · outbound

This paper cites L ong D oc URL : a Comprehensive Multimodal Long Document Benchmark Integrating Understanding, Reasoning, and Locating.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents L ong D oc URL : a Comprehensive Multimodal Long Document Benchmark Integrating Understanding, Reasoning, and Locating

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:28.780194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:28.780194Z digest=sha256:60a4af96f369e2e52293dfe914e879ceccfeb53458dbdc2dd5b78524f3839316

Observation be39bc49-bc04-445a-889f-1b244acaad77 · outbound

This paper cites Marathon: A Race Through the Realm of Long Context with Large Language Models.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Marathon: A Race Through the Realm of Long Context with Large Language Models

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:28.944679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:28.944679Z digest=sha256:94346fc56835f5099b3d6154f452b5c922b568a2e8c0071b9f3a3fbf53b50618

Observation fd222f99-07e2-42ec-a6ef-3e0c9ccdb251 · outbound

This paper cites LONGAGENT : Achieving Question Answering for 128k-Token-Long Documents through Multi-Agent Collaboration.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents LONGAGENT : Achieving Question Answering for 128k-Token-Long Documents through Multi-Agent Collaboration

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:29.124793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:29.124793Z digest=sha256:70df682cbbaa86aa259ec443fcac6ee3042ec93d36bb49ad8028efdaedb2a238

Observation ee9968ae-5863-4866-ba4b-33f3b17f2f0b · outbound

This paper cites Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 , pages =.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 , pages =

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:29.276413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:49:29.276413Z digest=sha256:a0564f2e1a774105e0dbdc7e8eccaa4baa2c1d1dece725b3c47444d32480f366

Observation 41ed5e38-1ea7-4f28-9cc1-7baf895ea063 · outbound

This paper cites 2021 , url=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents 2021 , url=

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:32.021891Z

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.

source=arxiv_source observed=2026-08-07T05:49:29.428072Z digest=sha256:acd4787539a595b8442ec5438e98465fa61296ca54221d53cd94a1eaa982f0fd

Observation 3d48fa26-701c-4809-9d04-b57dbd0d22fb · outbound

This paper cites Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence , pages=.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence , pages=

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:31.707433Z

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.

source=arxiv_source observed=2026-08-07T05:49:29.568963Z digest=sha256:840aa41e2df4b1fa05bdd549adde74f615ec1681bfff945948b42967eb0e2288

Observation 76d5f9b3-44d6-4c85-86d9-413eaba4932f · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , pages =.

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents Proceedings of the AAAI Conference on Artificial Intelligence , pages =

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:49:31.439432Z

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.

source=arxiv_source observed=2026-08-07T05:49:29.665310Z digest=sha256:5482a3c12b8fadc3037675f3acd9926c0158aadcf02ea33ee9732e8665e58d99

Pith citing papers

No inbound Pith citation observations are available.