{"as_of":"2026-08-21T23:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:71b3ca7ec89ca4c39bce102e1e4518586c285e70ff3c270a4b65bc2ac8965974","coverage":[{"denominator":61,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":61,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:49:29.665310Z","state":"measured"},{"denominator":61,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":61,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2608.06312/citation-record","integrity":"/paper/2608.06312/integrity","json":"/paper/2608.06312/citation-record.json","paper":"/paper/2608.06312"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.12191","last_updated":"2024-10-03T15:54:49Z","snapshot_observed_at":"2026-08-06T05:35:29.109022Z","submitted_at":"2024-09-18T17:59:32Z","title":"Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.12191","snapshot_observed_at":"2026-08-07T05:49:21.426003Z","title":"arXiv preprint arXiv:2409.12191 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:21.426003Z"},"links":{"cited_paper":"/paper/2409.12191","citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:c755f0c41e906908d4dbc7cf51463166fac1b0ea3bb5d29fb18d12e4b8d05ac5","observation_id":"b37b6b9a-8584-4f6c-a980-a15d897d638e","resolution":{"observed_at":"2026-08-07T05:49:21.426003Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.12966","last_updated":"2023-10-13T02:41:28Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-08-24T17:59:17Z","title":"Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.12966","snapshot_observed_at":"2026-08-07T05:49:21.587773Z","title":"arXiv preprint arXiv:2308.12966 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:21.587773Z"},"links":{"cited_paper":"/paper/2308.12966","citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:b9666ce5867218af128a9e5edafb4731bfe125491e020e84803e87c49ed5e790","observation_id":"bd19dba9-daab-4af5-a676-27a0c8874d44","resolution":{"observed_at":"2026-08-07T05:49:21.587773Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.15383","last_updated":"2025-01-26T03:47:25Z","snapshot_observed_at":"2026-08-17T05:35:17.658314Z","submitted_at":"2025-01-26T03:47:25Z","title":"Qwen2.5-1M Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.15383","snapshot_observed_at":"2026-08-07T05:49:21.792007Z","title":"arXiv preprint arXiv:2501.15383 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:21.792007Z"},"links":{"cited_paper":"/paper/2501.15383","citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:b62d7cfd48cd8de446b4d77ecd78c85ee6325825e93cad266c00f5938a1191e4","observation_id":"92fb491b-8fd4-4a51-979f-0f82a19fcf67","resolution":{"observed_at":"2026-08-07T05:49:21.792007Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.26494","last_updated":"2026-07-30T05:04:36Z","snapshot_observed_at":"2026-08-19T15:59:30.898415Z","submitted_at":"2026-05-26T03:16:11Z","title":"The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.26494","snapshot_observed_at":"2026-08-07T05:49:21.906429Z","title":"arXiv preprint arXiv:2605.26494 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:21.906429Z"},"links":{"cited_paper":"/paper/2605.26494","citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:f6894060fd0fc65bb255292dfcdf51a487db858a0efe5d26424fbe6c799f1a15","observation_id":"8284316d-0863-44f2-82db-9e83188366f6","resolution":{"observed_at":"2026-08-07T05:49:21.906429Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:22.042799Z","title":"arXiv preprint arXiv:2606.19348 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:22.042799Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:8f564bb80b1fb2ac893499f2f123343a75f5bc18c8635fcee14fc1922685755c","observation_id":"80cfdfbf-6077-431e-874c-c387e22c91dd","resolution":{"observed_at":"2026-08-07T05:49:22.042799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.09388","last_updated":"2025-05-14T13:41:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-14T13:41:34Z","title":"Qwen3 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.09388","snapshot_observed_at":"2026-08-07T05:49:22.171137Z","title":"arXiv preprint arXiv:2505.09388 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:22.171137Z"},"links":{"cited_paper":"/paper/2505.09388","citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:d56509137f4123b12db7f6cc4d3fd167e34eb918cdb71f04ea2c094b2c8b8293","observation_id":"59b0843f-8750-4016-b0e9-f8640e2261d6","resolution":{"observed_at":"2026-08-07T05:49:22.171137Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:22.297590Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:22.297590Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:8abc83a0183118cdaaaf6fb0879a04e392b401afb5ead9709c45949e833912bd","observation_id":"b630b7ca-6ffc-431b-9edd-fdf5e481aca6","resolution":{"observed_at":"2026-08-07T05:49:22.297590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:36.428104Z","title":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=","venue":null,"work_id":"ead6c563-69c9-4b6f-ac12-92c69a8f082c","year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:22.419479Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:8d6d9004440be402e8c48c1a4f1910c2c2f64ce238c9a289be4193d17b36846f","observation_id":"c4a4b59a-ac4d-4c09-a082-7f7bea8394e3","resolution":{"observed_at":"2026-08-07T05:49:36.529940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:22.477170Z","title":"Proceedings of the 2024 conference on empirical methods in natural language processing , pages=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:22.477170Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:7f3727c446c61df1130a6af035f61e43db279f5e39bd70e53cf5c56e6215f379","observation_id":"3c174370-f9db-4992-871d-6e304f3ff8f6","resolution":{"observed_at":"2026-08-07T05:49:22.477170Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:22.599267Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:22.599267Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:6d78ac6f522626c13bfc3313381cc93f28320c28b4fade5da19ce14e9da370ce","observation_id":"9aba8d10-e3a3-4def-9019-6400ed2ab84d","resolution":{"observed_at":"2026-08-07T05:49:22.599267Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.11944","last_updated":"2023-11-20T17:28:02Z","snapshot_observed_at":"2026-08-13T18:35:52.271946Z","submitted_at":"2023-11-20T17:28:02Z","title":"FinanceBench: A New Benchmark for Financial Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.11944","snapshot_observed_at":"2026-08-07T05:49:22.717449Z","title":"arXiv preprint arXiv:2311.11944 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:22.717449Z"},"links":{"cited_paper":"/paper/2311.11944","citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:e3adc5b2babc7f71e9ede60c1ebc0bf70b940e11a5e7c55bd17378c3864299a0","observation_id":"2fdf6f0f-c378-45cf-864d-ec74793a0c1b","resolution":{"observed_at":"2026-08-07T05:49:22.717449Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:36.167466Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":"30f12596-f58d-43fe-9289-ca887581bc53","year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:22.839136Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:76733f11b4e24bc1fc221d30dac5c55f27f26b459e35da97930fda4841a438b2","observation_id":"47f26a0f-fd5e-4fb8-89c7-209bae63279e","resolution":{"observed_at":"2026-08-07T05:49:36.221633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:35.994436Z","title":null,"venue":null,"work_id":"e726c422-0666-44a1-b72e-a2267daf0d61","year":2025},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:22.990288Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:53ff3fcfd4e22f1cb708b3893fc9ab7eb372879b517e775d387e4cf52ab6ff49","observation_id":"a2cbf0e8-2070-49ed-9a0e-518ab9390502","resolution":{"observed_at":"2026-08-07T05:49:36.086564Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:35.770535Z","title":"Findings of the Association for Computational Linguistics: ACL 2024 , pages=","venue":null,"work_id":"7681de27-b5d7-4f04-9ac0-bf1c1547223d","year":2024},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:23.110667Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:1b87be61abdb1c87fad1a002eec56a361db18c2ff9d025ef9d0d8bb1ccd41d35","observation_id":"1f3d1138-35dc-4b92-ae7d-067bca1052a1","resolution":{"observed_at":"2026-08-07T05:49:35.848745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:35.566373Z","title":"Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) , pages=","venue":null,"work_id":"42abd7e7-1f5e-4b02-abc8-9e42e9b75fa7","year":2024},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:23.254352Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:59decec1b6a8d84d03ec928f69fc373b6fd798eeb202e9adf237e5bae76f7b99","observation_id":"b98f823e-a5c1-410b-a8ed-15b414286bd2","resolution":{"observed_at":"2026-08-07T05:49:35.657836Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2025.04001","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:30.832617Z","title":"Journal of Artificial Intelligence Research , author=","venue":null,"work_id":"fd7a7c66-bc62-44dc-9f2b-d1f1fb124be5","year":2025},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:23.304807Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:2302e1ae0a3c3cb42c76db1482c9785d045cd24909c56f9130305a03ab05fa99","observation_id":"41b49ea8-bfa2-48d4-abef-ea158fbca7c5","resolution":{"observed_at":"2026-08-07T05:49:31.002254Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.00445","last_updated":"2022-05-01T11:01:28Z","snapshot_observed_at":"2026-08-17T19:53:31.995761Z","submitted_at":"2022-05-01T11:01:28Z","title":"MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.00445","snapshot_observed_at":"2026-08-07T05:49:23.473812Z","title":"arXiv e-prints , keywords =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:23.473812Z"},"links":{"cited_paper":"/paper/2205.00445","citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:9e1a7ccf401f3509f21c77afb8f4489fd4cde2c142a0b2e2813ee6df3affce7b","observation_id":"4ec7759e-b5f4-45c8-b190-84700ff4e436","resolution":{"observed_at":"2026-08-07T05:49:23.473812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:23.580799Z","title":"The Eleventh International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:23.580799Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:7f2f39289e2a4fbbf164769f252a04520df00d311e2e3d9cd27c54487b8f2eda","observation_id":"3d5afadd-873b-45c2-9a3f-c8c228fae72c","resolution":{"observed_at":"2026-08-07T05:49:23.580799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:23.681253Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:23.681253Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:f37d45871e4154f5ae480b238c9a3df0043372961d9b3e4123afac01a7ac5f4f","observation_id":"466d58f9-4e69-4b7c-8028-ba8840fdb24f","resolution":{"observed_at":"2026-08-07T05:49:23.681253Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15334","last_updated":"2023-05-24T16:48:11Z","snapshot_observed_at":"2026-08-20T10:31:15.813764Z","submitted_at":"2023-05-24T16:48:11Z","title":"Gorilla: Large Language Model Connected with Massive APIs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15334","snapshot_observed_at":"2026-08-07T05:49:23.853606Z","title":"URL https://arxiv","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:23.853606Z"},"links":{"cited_paper":"/paper/2305.15334","citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:2db3f830ffc32b80b4f69c68a0c56a9aec8c34f5cde8820e0885af7ff3f18998","observation_id":"87782e9f-23b8-446e-a42f-fe0afb16d460","resolution":{"observed_at":"2026-08-07T05:49:23.853606Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:23.957081Z","title":"International Conference on Learning Representations , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:23.957081Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:97f0be2ec89ebb1af56aa72735fc96c96ac2b877ff405b3478e4b03c601f55d5","observation_id":"96ccf7ed-6252-41c9-8e5d-24e4c0350a08","resolution":{"observed_at":"2026-08-07T05:49:23.957081Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:24.101295Z","title":"AutoGen: Enabling Next-Gen","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:24.101295Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:730838e4811561184602719e0091b0c0dc6fb40bdf2ab2e6d3cb9f08ac350f14","observation_id":"35f5cad1-29da-44c4-8384-2a8dd1edc1f0","resolution":{"observed_at":"2026-08-07T05:49:24.101295Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.17541","last_updated":"2024-06-20T02:53:20Z","snapshot_observed_at":"2026-08-20T01:32:52.941685Z","submitted_at":"2023-11-29T11:23:42Z","title":"TaskWeaver: A Code-First Agent Framework","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.17541","snapshot_observed_at":"2026-08-07T05:49:24.214318Z","title":"arXiv preprint arXiv:2311.17541 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:24.214318Z"},"links":{"cited_paper":"/paper/2311.17541","citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:2c2c76555254fb7bccdfbdead3c3fb496adad76cc80f81963d08cba03a57024e","observation_id":"2d4f6248-2e21-4611-9e32-a56ce8cda2ff","resolution":{"observed_at":"2026-08-07T05:49:24.214318Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:24.354531Z","title":"International Conference on Learning Representations , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:24.354531Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:44753f767112dec3090c4b681ee0b3003681ae10113c4bbfd9ebaae7973c0bca","observation_id":"c35b6044-3b53-4072-99e0-ade721890492","resolution":{"observed_at":"2026-08-07T05:49:24.354531Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:35.268026Z","title":"27th USENIX Security Symposium (USENIX Security 18) , pages=","venue":null,"work_id":"f05f26eb-6b0f-424e-bf63-7e5e0a49b482","year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:24.496458Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:8de2d8fd128db256eaa337d9f73cbde0ee0408f8d7f2211da19ad9be968c9c18","observation_id":"703149a1-8c74-40fc-a9a4-db07354d1a1c","resolution":{"observed_at":"2026-08-07T05:49:35.359609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:35.047056Z","title":null,"venue":null,"work_id":"9d1fa912-effa-46e8-b693-5ccb338f9964","year":2019},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:24.617899Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:231d5ef81980ecc6ae835b237d2846f01a4c5d1a7b687411c097226db22a1b5b","observation_id":"52a455d7-b3e0-4f7d-819e-f1bac2772824","resolution":{"observed_at":"2026-08-07T05:49:35.129594Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:34.706398Z","title":"Findings of the Association for Computational Linguistics: EMNLP 2020 , pages=","venue":null,"work_id":"972bc1b9-7262-4baa-874f-47362e538c7f","year":2020},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:24.754758Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:31ff753b2e7c77bbd495015719624fe4ec353e5771eb10d703112532a42bc59c","observation_id":"979ee601-0b57-4618-a153-621512fefc75","resolution":{"observed_at":"2026-08-07T05:49:34.889133Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:34.461306Z","title":"IEEE Transactions on Software Engineering , volume=","venue":null,"work_id":"d0a99ac4-0744-431f-8552-41ce08c11cd0","year":2023},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:24.875193Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:9a9773b6e4e1dede72f0705710a2b055fbc6a535f5376472fe68e103a664522a","observation_id":"f60bf87b-bb7e-405d-a00e-09e3aa494843","resolution":{"observed_at":"2026-08-07T05:49:34.597353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:34.261144Z","title":"ACM Computing Surveys (CSUR) , volume=","venue":null,"work_id":"f0615326-d5de-4cce-bf8e-18a4cdfd1d23","year":2021},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:25.025546Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:7b4e813c13b4c41242e8215b5fd1a9378be9abf06282f2102453830e8834709d","observation_id":"4733c1ea-477e-4983-86d6-43eaf372d376","resolution":{"observed_at":"2026-08-07T05:49:34.347062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:34.034626Z","title":"txt, a cheap Shallow Parsing approach for Regulatory texts , author=","venue":null,"work_id":"8278ac8e-52f3-4fe4-8b21-2a85aea5b12d","year":2021},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:25.122241Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:63db5b4758bb585f5f1b2535fd0e98df0cf7e38f3e11133d3a6fd1c575044606","observation_id":"1cd4c3b9-b3a1-48ea-9307-d402208c8433","resolution":{"observed_at":"2026-08-07T05:49:34.120058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:25.284368Z","title":"Scientific data , volume=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:25.284368Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:e49803ffdeced86d4d5e2e38ce5b2c08c2fbd6ba83e6b34afff7f733918bfa3c","observation_id":"51c5e303-25ce-4e2d-bb93-ae9122af5925","resolution":{"observed_at":"2026-08-07T05:49:25.284368Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:25.427561Z","title":"arXiv preprint arXiv:2603.23519 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:25.427561Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:59959c8c1bba871df052ce46ba56155ad1d5de60b19f512c31ba1328ed68e33e","observation_id":"f4c3eb73-51d7-4ea9-a357-82a34af1f394","resolution":{"observed_at":"2026-08-07T05:49:25.427561Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:33.852279Z","title":"Proceedings of the AAAI Conference on Artificial Intelligence , volume=","venue":null,"work_id":"d6b00fe0-4870-48c2-97ba-12c4fe58ce71","year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:25.598133Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:a54934eef739a28c44191b97395a361f37420b76b3ea4ca503adf19ae0d4041e","observation_id":"ef29c3c1-c174-4a35-82f4-bdaa05fa2d07","resolution":{"observed_at":"2026-08-07T05:49:33.951222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:33.611179Z","title":"IEEE access , volume=","venue":null,"work_id":"4b0b5f52-ba44-4111-b34a-bc649d8cef4a","year":2024},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:25.730365Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:bb0d779f1dbd555fc36d486083593aed2a7bd0f48ccc6b8bccdecdac9626d1a5","observation_id":"512d389f-089d-4e7f-87fe-b24af1f95f30","resolution":{"observed_at":"2026-08-07T05:49:33.699240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:25.883922Z","title":"Proceedings of the 62nd annual meeting of the association for computational linguistics (volume 1: Long papers) , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:25.883922Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:311c8f932848af8bf9e10bfbc35c2452b389a80b3fa7680f11ceef5b480e76d7","observation_id":"a4c44893-cfa7-4c47-baba-d55b18892a61","resolution":{"observed_at":"2026-08-07T05:49:25.883922Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.02324","last_updated":"2025-08-04T11:49:20Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-04T11:49:20Z","title":"Qwen-Image Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.02324","snapshot_observed_at":"2026-08-07T05:49:26.030021Z","title":"arXiv preprint arXiv:2508.02324 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:26.030021Z"},"links":{"cited_paper":"/paper/2508.02324","citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:f002d60bb95526bc76b75c2ee13c6189b3149ccaf0b6c42fcc0af802549f76c5","observation_id":"a012409d-df1a-40f6-ad11-7264d22f3202","resolution":{"observed_at":"2026-08-07T05:49:26.030021Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:33.369884Z","title":"Proceedings of the AAAI Conference on Artificial Intelligence , volume=","venue":null,"work_id":"bd3d668d-0b04-4e73-856c-e60a1eb6d360","year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:26.100249Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:55e58924728ef53f9cd7e719324713edab68c2e01a070bba1f5a721a574dc7a3","observation_id":"de703f0b-4940-4d19-abe1-5f57d4f70b4a","resolution":{"observed_at":"2026-08-07T05:49:33.471774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2605.10267","last_updated":"2026-05-13T06:35:15Z","snapshot_observed_at":"2026-08-19T06:07:20.577183Z","submitted_at":"2026-05-11T09:30:48Z","title":"IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.10267","snapshot_observed_at":"2026-08-07T05:49:26.272401Z","title":"arXiv preprint arXiv:2605.10267 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:26.272401Z"},"links":{"cited_paper":"/paper/2605.10267","citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:8ebff9d291e8ab0a037bae2601f3be3f921a701e313d2823c2076a19d258754d","observation_id":"ffa1beb4-6f22-4071-bb82-b6c6eb196cbe","resolution":{"observed_at":"2026-08-07T05:49:26.272401Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.16400","last_updated":"2025-06-19T15:31:29Z","snapshot_observed_at":"2026-07-06T21:44:52.595410Z","submitted_at":"2025-06-19T15:31:29Z","title":"Physical-Layer Signal Injection Attacks on EV Charging Ports: Bypassing Authentication via Electrical-Level Exploits","version":1},"cited_work":{"arxiv_id":"2506.16400","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.16400","snapshot_observed_at":"2026-08-07T05:49:30.358860Z","title":"Physical-Layer Signal Injection Attacks on EV Charging Ports: Bypassing Authentication via Electrical-Level Exploits","venue":"cs.CR","work_id":"167216b3-6af6-4d06-9ac3-05fd1da7fd1e","year":2025},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:26.400199Z"},"links":{"cited_paper":"/paper/2506.16400","citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:a412435bc00c8a22f83690fe7036ef577d842226bac3e0a965cc1a9034c30c74","observation_id":"02b65240-d639-49a1-9b42-c69f69d3c874","resolution":{"observed_at":"2026-08-07T05:49:30.511176Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:26.504189Z","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models , url =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:26.504189Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:8544db9a91763c7638dc22c232857ca5e6122409143e1fa5f85b3a1ee9826970","observation_id":"242de829-b719-45be-9f7b-b5082b603965","resolution":{"observed_at":"2026-08-07T05:49:26.504189Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:26.642090Z","title":"The Eleventh International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:26.642090Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:9d844ee3bcf6088752e773011eac0f1d4f88963b118d42b5991900c5620d75c8","observation_id":"f172a2cf-2dfc-4a2e-957d-28faa14bc159","resolution":{"observed_at":"2026-08-07T05:49:26.642090Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:26.760835Z","title":"Training language models to follow instructions with human feedback , url =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:26.760835Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:5cf617995ab2153c62ae21b403cecce6a303d9f61400f8df0814916c004cfc91","observation_id":"306b460d-25b3-497c-8070-96873e6f248c","resolution":{"observed_at":"2026-08-07T05:49:26.760835Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:26.887268Z","title":"L -Eval: Instituting Standardized Evaluation for Long Context Language Models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:26.887268Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:1f378e6e45622c61e23c043c531af54fc0e9676f56c23b78f71c7c9d7c910265","observation_id":"c2ea905e-d121-4c2c-a2ed-9093b0fef070","resolution":{"observed_at":"2026-08-07T05:49:26.887268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:27.036670Z","title":"2024 , url=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:27.036670Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:7321d15bd2f92cdcc8d8be0a5e8fcb47a1bbf5e82ea774c356214a1acef40dcd","observation_id":"a2893ee0-873e-4f2c-b6df-5752ca009e71","resolution":{"observed_at":"2026-08-07T05:49:27.036670Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:33.148555Z","title":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=","venue":null,"work_id":"b66c74cd-0e81-40b8-84dd-4c6be2613348","year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:27.219944Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:f0a7acf38b1746b68f973b06c609325a92c53841b5b7b6949c1c6effd41d49fd","observation_id":"795929a7-6e76-4f86-815b-62c60dbc1b66","resolution":{"observed_at":"2026-08-07T05:49:33.247361Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:32.922076Z","title":"The Twelfth International Conference on Learning Representations , year=","venue":null,"work_id":"aa086a7d-8070-4ae2-be18-3a01c564c998","year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:27.346997Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:3aec1fd185b88e225108f2dd886b72f1b178f844ef91725accbed77299d5c2f7","observation_id":"ecbbfaf4-7382-4eb5-81d4-a6e294d8bce3","resolution":{"observed_at":"2026-08-07T05:49:33.005112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:27.481197Z","title":"Findings of the Association for Computational Linguistics: EMNLP 2021 , pages=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:27.481197Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:7dffb9cb0ed5a6e51e00eccacda2b425adeeaafc33e9f558bc479eae216f6c9c","observation_id":"1e5fe0e4-6e43-4227-b72b-a17bcc82f408","resolution":{"observed_at":"2026-08-07T05:49:27.481197Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:27.653428Z","title":"and Gardner, Matt","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:27.653428Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:9d39ae72128cc1737737ea8d2dd85e9b1905345e34855389d1cf48a65cfb19c4","observation_id":"75141fb6-23de-496d-b27d-44c0aca8683c","resolution":{"observed_at":"2026-08-07T05:49:27.653428Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2025.acl-long.1206","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"ACORD : An Expert-Annotated Retrieval Dataset for Legal Contract Drafting","venue":null,"work_id":"efa142b2-8761-47dc-bb5a-e8f400924f72","year":2025},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:27.790026Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:073d177230f7db0a3c1cb2b22d6d4e652d2c42b34e9e868875d0c654fc84622e","observation_id":"86bd0a3c-775e-4888-a8d5-af4b227376b3","resolution":{"observed_at":"2026-08-07T05:49:29.986176Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-15T01:08:19.372975+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-15T01:08:19.372975+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:32.679704Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":"730b06af-3cdc-4f36-a2bb-1450e7d96149","year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:27.921356Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:9847648fe734753b90140cc729c5f4600f5af69eba838e44b3f8e9aec8565326","observation_id":"8aad16ee-e78a-471b-bc75-66c812633682","resolution":{"observed_at":"2026-08-07T05:49:32.785964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:32.432928Z","title":"Proceedings of the 2018 conference of the North American chapter of the Association for Computational Linguistics: Human language technologies, volume 1 (long papers) , pages=","venue":null,"work_id":"8b56069d-bd96-4e0d-9264-dcaa43c18f83","year":2018},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:28.063746Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:6bc9df46561b87da200e0a18b9c5535bcf158d54e959d796c71e105ce8b45857","observation_id":"095c4c7f-a0a6-4fcd-9c84-9a6d94da84a5","resolution":{"observed_at":"2026-08-07T05:49:32.553618Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:32.212253Z","title":"Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=","venue":null,"work_id":"2dfb2225-c3df-4137-af32-e92654aff34f","year":2023},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:28.241869Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:9814f8f2e1e09c3b231bc571e99af44f8edd01af6c0883c21fd443ea6e11ac76","observation_id":"ae454bf9-16be-4ff2-80f4-b9f093308b00","resolution":{"observed_at":"2026-08-07T05:49:32.276411Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:28.453015Z","title":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:28.453015Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:c640e30dc9216e703aa21d6fdf302ee489f44f6dd4160de4aa29b6fc9a28e275","observation_id":"f0984ac8-6f3f-444b-923d-4ccaf755acbf","resolution":{"observed_at":"2026-08-07T05:49:28.453015Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:28.624966Z","title":"D oc M ath-Eval: Evaluating Math Reasoning Capabilities of LLM s in Understanding Long and Specialized Documents","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:28.624966Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:e84b33ddb35799989857ddb2f6d5d37384047d59b3e01fbf65d9d4a53dde4edf","observation_id":"8774cbed-a1af-4790-aeb9-6cb58f71064d","resolution":{"observed_at":"2026-08-07T05:49:28.624966Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:28.780194Z","title":"L ong D oc URL : a Comprehensive Multimodal Long Document Benchmark Integrating Understanding, Reasoning, and Locating","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:28.780194Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:7d8c793fb05213838a95e1e1b4cd9eb63cb94be18ae8734f1c976fbf2f2a6661","observation_id":"ef2ffef8-dae6-4c41-abe8-7f38a7643daa","resolution":{"observed_at":"2026-08-07T05:49:28.780194Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:28.944679Z","title":"Marathon: A Race Through the Realm of Long Context with Large Language Models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:28.944679Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:b903b8d6b12773d8ce279ce7c5db6dc14c4728cea2a40accee7a89b6a18d70be","observation_id":"be39bc49-bc04-445a-889f-1b244acaad77","resolution":{"observed_at":"2026-08-07T05:49:28.944679Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:29.124793Z","title":"LONGAGENT : Achieving Question Answering for 128k-Token-Long Documents through Multi-Agent Collaboration","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:29.124793Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:afa92170d440f5d53cbba206714d60d7b077ffe250856e01e81a744e1d061fa0","observation_id":"fd222f99-07e2-42ec-a6ef-3e0c9ccdb251","resolution":{"observed_at":"2026-08-07T05:49:29.124793Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:29.276413Z","title":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 , pages =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:29.276413Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:7aa3bd0ab0be1ce4179fddc5adca3b2a8fec37addf35e9e3b58b0e02cc2a4add","observation_id":"ee9968ae-5863-4866-ba4b-33f3b17f2f0b","resolution":{"observed_at":"2026-08-07T05:49:29.276413Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:31.898083Z","title":"2021 , url=","venue":null,"work_id":"1f3cdbc9-8bb2-4d4e-83ba-0faba225ad6f","year":2021},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:29.428072Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:7361f6df81ca61f62e1babda4a1f11239bee2ce2aae5339080825cf690295e9d","observation_id":"41ed5e38-1ea7-4f28-9cc1-7baf895ea063","resolution":{"observed_at":"2026-08-07T05:49:32.021891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:31.550023Z","title":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence , pages=","venue":null,"work_id":"4afdebe0-349a-4e7e-9af8-ace77e09093a","year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:29.568963Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:31937498f0446d37d7e5e8795f458a536c463d8bb47133855582128779045db5","observation_id":"3d48fa26-701c-4809-9d04-b57dbd0d22fb","resolution":{"observed_at":"2026-08-07T05:49:31.707433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:49:31.301869Z","title":"Proceedings of the AAAI Conference on Artificial Intelligence , pages =","venue":null,"work_id":"b6392db4-b44a-44b4-a71f-38104072ff01","year":null},"citing_paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-07T05:49:29.665310Z"},"links":{"citing_paper":"/paper/2608.06312"},"observation_digest":"sha256:8cc6ef5e62b3be8dd7e39c9b97cbae2d74646aa16552d3689362702bd9dfa932","observation_id":"76d5f9b3-44d6-4c85-86d9-413eaba4932f","resolution":{"observed_at":"2026-08-07T05:49:31.439432Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2608.06312","last_updated":"2026-08-06T17:27:23Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-18T05:21:38.883269Z","submitted_at":"2026-08-06T17:27:23Z","title":"Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents"},"reference_resolution":{"displayed":61,"state_counts":{"malformed_identifier":0,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":38,"verified_exact":1,"verified_fuzzy":20},"total_outbound_references":61},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2608.06312."}