{"as_of":"2026-08-21T03:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fa6b663476f43a7c4094034b0ddd3e894baefcec83efe3f29b01636d959d4db9","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T23:39:54.314250Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+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/2506.16831/citation-record","integrity":"/paper/2506.16831/integrity","json":"/paper/2506.16831/citation-record.json","paper":"/paper/2506.16831"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:39:54.641333Z","title":"Trustworthy AI: From Principles to Practices.ACM Computing Surveys, 55(9):1–46, September 2023","venue":null,"work_id":"13584d25-bd72-4678-a0a7-015cf25107c1","year":2023},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.235969Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:dd92f6bfdffb4bfa622770e2af451e1a7b7532813188722d9cf3825163a58f86","observation_id":"ca9969e9-ea86-4303-8f3b-d5d5550f2f64","resolution":{"observed_at":"2026-08-06T23:39:54.644015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.633851Z","title":"Bogen and A","venue":null,"work_id":"c79b4ee1-1e4a-4da0-9f0c-e984db4f8fed","year":2018},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.239258Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:80bc4751b38e1a724ce8f837bbed96c3c334681e49b30cd9c29b7e3e88da6e40","observation_id":"a33c688e-3e46-4ace-a6d6-3c6b481a3ddf","resolution":{"observed_at":"2026-08-06T23:39:54.636325Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.626320Z","title":"Boudette","venue":null,"work_id":"539ddf27-e484-4ce6-bbdf-a0bfa0162b04","year":2021},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.242948Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:e1e63b87da9c6acf1614d8564faa4bc8a7eaef1a7c0cfd7020f58a6b4043c259","observation_id":"2324c490-bb8f-4baf-b311-9dd654988090","resolution":{"observed_at":"2026-08-06T23:39:54.628788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.618927Z","title":"https://www.carnegiecouncil.org/explore-engage/key-terms/ai- governance","venue":null,"work_id":"079d2eb4-89d3-42fb-bcb0-ed7b76c1de5e","year":null},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.247811Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:a39ac50988b8da2c54ef0fbd68b3d89d0eb739a55f6e2d26fc0b95dbbd9002af","observation_id":"0f248ea7-a393-426c-9477-3972d043e227","resolution":{"observed_at":"2026-08-06T23:39:54.621601Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.611621Z","title":null,"venue":null,"work_id":"a8cbe281-1453-4c3a-b4ac-d14874683740","year":2023},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.251487Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:8214e1ab3d79faa6c9c5cc7a69c71a1067c8b3ee85c076cf7a45a7452685ab29","observation_id":"47c7b443-e372-456e-9a57-874a6880159b","resolution":{"observed_at":"2026-08-06T23:39:54.614153Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.603710Z","title":"Oxford University Press, August 1997","venue":null,"work_id":"37c6a9e4-4038-4cde-b0f4-360115029a53","year":1997},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.254895Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:4b7c986c902639633eec27985b30c7eae8aae7e74c5af9d4b228194ca057fbfa","observation_id":"9b812558-ff54-4a21-a5d6-1f659b295663","resolution":{"observed_at":"2026-08-06T23:39:54.606486Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.595067Z","title":"Microsoft Press, Redmond, Washington, second edition edition, 2004","venue":null,"work_id":"a956697d-516a-40ca-a581-ca2c2262ddc1","year":2004},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.257893Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:0c2648a371fdc931d217718332f160fcaee91c91d9d40229aa394c15edd77ce3","observation_id":"d0191da4-eeb7-44fe-9be4-cc8e4df20bde","resolution":{"observed_at":"2026-08-06T23:39:54.598143Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.587033Z","title":"https://bertrandmeyer.com/oosc2/","venue":null,"work_id":"af7121cc-7105-48cf-b016-5a2b5ad562a3","year":null},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.260621Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:911b6bc5d3e190537159832663a1ee3609b8ecbeb9258e588c82262f973fd53d","observation_id":"fa068335-e3b2-46b5-a480-0cb10bcbf4bc","resolution":{"observed_at":"2026-08-06T23:39:54.589730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.579508Z","title":null,"venue":null,"work_id":"3a95b1ae-ab56-4847-b64b-7e778aff69b4","year":2021},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.263187Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:7d3b2d931e8407b9e1df3345000836068803f92c26d6b31c82e085b725b5303d","observation_id":"fd637eb5-0ee2-4180-b3c1-a9934c6ba281","resolution":{"observed_at":"2026-08-06T23:39:54.582017Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.571669Z","title":null,"venue":null,"work_id":"d4b5a861-c587-4821-a8a4-1fd5db183d5a","year":2018},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.265701Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:1f34b50a8323703f313c1e625fd9f5900d59c40216e6e1068fff39629f29cdf0","observation_id":"47a7b59f-4b77-4f04-8cfb-dcab74e77b7a","resolution":{"observed_at":"2026-08-06T23:39:54.574488Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.563348Z","title":"Towards Account- ability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure","venue":null,"work_id":"c4ed395e-82ec-4f3a-a249-50e0795bfd71","year":2021},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.268156Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:6dd1de7ce8453157d1429579d0852978f92a1de2893b38a8a9e8ea3a7416ac2f","observation_id":"98d34292-d66d-4609-9bb9-a4e923b6bdea","resolution":{"observed_at":"2026-08-06T23:39:54.566233Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.551068Z","title":"Reliability, Robustness, and Resilience: The R3 Concept in Machine Learning Inference, July 2023","venue":null,"work_id":"3c46bd02-a4dc-4d2f-8191-d47d27a3728d","year":2023},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.277768Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:7bde8313b9f7fa7424419152eb0b41a74768f21d3057bed1e88d7a0c32220d56","observation_id":"80913107-fc48-4b27-8c1e-af36a25eccbb","resolution":{"observed_at":"2026-08-06T23:39:54.553733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.543434Z","title":"https://encord.com/blog/model- robustness-machine-learning-strategies/","venue":null,"work_id":"b24acaf4-7bed-4a7c-ba47-5404c1a16e91","year":null},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.280510Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:48bde733fb171e7bc5ef59c8b20c47ab9a95bcab9781a759db5c2710c4dee2b2","observation_id":"a383f745-4dd4-433f-a51a-0a8874cc2bf2","resolution":{"observed_at":"2026-08-06T23:39:54.546309Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.536504Z","title":"Freeman, and Xinwei Deng","venue":null,"work_id":"bae456d9-4be8-4398-bfb7-26fd6acf03e8","year":2023},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.283051Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:c6089ad8d45fe17376121297d2e855b6ce8f45706070beb99e5b6ad396fb9c98","observation_id":"2e80d294-b214-4d25-b8d9-40eccb0a1312","resolution":{"observed_at":"2026-08-06T23:39:54.538826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.529689Z","title":"Blood, Nathan W","venue":null,"work_id":"16396fc1-67fe-49af-bb80-46fd13cdaa76","year":2023},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.285864Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:3a938b6f0c97be84001dfa70527dbe32b82bf3cabe0b5db7c4e2d807f126a428","observation_id":"cf85f060-2cde-41fe-8c57-203345119f85","resolution":{"observed_at":"2026-08-06T23:39:54.532142Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.522464Z","title":"Trustworthy and Robust AI Deployment by Design: A framework to inject best practice support into AI deployment pipelines","venue":null,"work_id":"e744edee-31cd-4048-b10b-08fc5ae550be","year":2023},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.288180Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:3de5c09df2adfbeefe24c1112630dc4bfe92c2da55ac93d3133429611bfa0ac4","observation_id":"9edf3d07-ecfb-4ff3-a85b-c214d246d644","resolution":{"observed_at":"2026-08-06T23:39:54.525133Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.514988Z","title":"AI Maintenance: A Robustness Perspective.Com- puter, 56(2):48–56, February 2023","venue":null,"work_id":"a6e6b2fe-31b3-44cf-ba28-163b1a726f9d","year":2023},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.290504Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:13c2858210ea420ca61e99ca33514171312213223828eec296e587b6d85f9d6f","observation_id":"c2ed98a6-3c29-42ec-a13b-3b2a393e3e50","resolution":{"observed_at":"2026-08-06T23:39:54.517762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.507205Z","title":null,"venue":null,"work_id":"8a121327-2c7e-49b6-b892-5a6bfd4306b3","year":2023},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.292912Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:34f87f28c945ffac1e9e574de72021a6fd7f07975b93c5f0059f9e28c7313b07","observation_id":"ae8c3af0-a8ad-42c6-8140-071e0df20f0d","resolution":{"observed_at":"2026-08-06T23:39:54.509561Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.499623Z","title":"White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, and Parker Barnes","venue":null,"work_id":"c91df1e7-a9c8-407b-98e2-151022e4533d","year":2020},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.295414Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:deb3a68b85c788c9049a844c035f32c359bcf66ecd4ac4a7dbb9c332841daad4","observation_id":"0d22d07a-c9b9-4d6d-b6f4-7d19fcf71283","resolution":{"observed_at":"2026-08-06T23:39:54.502230Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.492190Z","title":"Machine Learning Op- erations(MLOps):Overview,Definition,andArchitecture","venue":null,"work_id":"61aa8025-91f4-4a15-b6c3-c7d689d0fdf3","year":2023},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.297765Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:557674d413578a090228356193718e277ef8ec702716837353bcafe5d8d6d32b","observation_id":"92f9f4b7-b752-4793-98ba-f8398229fab2","resolution":{"observed_at":"2026-08-06T23:39:54.494928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.483710Z","title":"AI governance in the system development life cycle: Insights on respon- sible machine learning engineering","venue":null,"work_id":"2ac57465-ab2f-44e6-8762-b82767a37000","year":2022},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.299889Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:bdfa2d8d517004c93ab1e928a4221a3b3c8952964793d38d17fd460226bf97d4","observation_id":"e3eb0309-ac18-4bc4-9b41-8e0d7a759429","resolution":{"observed_at":"2026-08-06T23:39:54.486705Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.474824Z","title":"Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges","venue":null,"work_id":"df133dbd-a203-4b8d-85e5-ae64479a1844","year":2021},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.302264Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:b068e5ce4554da809c996a90c48a9f3768580ed5a9528d80ce33e8d4a77d3c91","observation_id":"9995d571-a2c3-429d-acdb-aa5dab38ad93","resolution":{"observed_at":"2026-08-06T23:39:54.477826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.374533Z","title":null,"venue":null,"work_id":"9872ea9b-581c-4abe-934b-1d973207090b","year":2023},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.304747Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:0dd18b84976b23035dc1c23394190bcdc66196754fdf2c907b7e013f04958927","observation_id":"af09e1d3-ef62-4862-9871-570082cbc414","resolution":{"observed_at":"2026-08-06T23:39:54.377402Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.365845Z","title":"MLOps as Enabler of Trustworthy AI","venue":null,"work_id":"24c130d3-5ed2-4ed5-8e97-afddb5160c10","year":2024},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.307108Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:54ea86d3561b1ff2f6d12983d809cc3cfd863b5cee41764439a03a8a640ecd9f","observation_id":"0e3df5a5-f8ef-4bfe-94d8-da46eedfba27","resolution":{"observed_at":"2026-08-06T23:39:54.369178Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.356502Z","title":"QoA4ML - A Framework for Supporting Contracts in Machine Learning Services","venue":null,"work_id":"9cbfdcb7-223b-4b03-862c-d60966614d10","year":2021},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.309372Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:5c711ade79da2ffd3d5467973d78046c3f5c5143e86c8a512f56aad1ec65de98","observation_id":"cc69c476-ed18-47df-8da4-6da135c959a2","resolution":{"observed_at":"2026-08-06T23:39:54.360164Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-06T23:39:54.346573Z","title":"Design by Contract for Deep Learning APIs","venue":null,"work_id":"41448b5c-3204-4243-a786-f148e2098c0d","year":2023},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.311893Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:67cd9ab7247887be1c3be22a8835b3d9c219e46cea2f8c0ae5b38afacfb09211","observation_id":"14408d92-1dd3-4e9e-97df-b55425361e0d","resolution":{"observed_at":"2026-08-06T23:39:54.351066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14231","last_updated":"2023-12-21T18:37:43Z","snapshot_observed_at":"2026-08-17T20:53:38.393384Z","submitted_at":"2023-12-21T18:37:43Z","title":"Building Your Own Product Copilot: Challenges, Opportunities, and Needs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.14231","snapshot_observed_at":"2026-08-06T23:39:54.314250Z","title":"https://arxiv.org/abs/2312.14231","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.314250Z"},"links":{"cited_paper":"/paper/2312.14231","citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:8bc2f566e57c7d17745a2157ea1a12fea00599e8e94b25a06076b607787bf4a2","observation_id":"b117067f-e047-45c1-9062-f7eb55c43820","resolution":{"observed_at":"2026-08-06T23:39:54.314250Z","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":"2026-08-06T23:39:54.274836Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-06T23:39:54.274836Z"},"links":{"citing_paper":"/paper/2506.16831"},"observation_digest":"sha256:baae1cd63ee883dc359d7b1cf9d7f1e36bf84ecac59b0704f7597410b292d568","observation_id":"2913102a-0f7d-400c-9a92-7b32c577af25","resolution":{"observed_at":"2026-08-06T23:39:54.274836Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.16831","last_updated":"2025-06-20T08:35:11Z","latest_version":1,"primary_category":"cs.SE","snapshot_observed_at":"2026-08-14T17:22:02.774763Z","submitted_at":"2025-06-20T08:35:11Z","title":"Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":0,"verified_fuzzy":21},"total_outbound_references":28},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2506.16831."}