{"as_of":"2026-08-08T07:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ba08c0a466253db569cff6d775e4ac6f354928c2add18e067bc65a3f49f815bd","coverage":[{"denominator":55,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:38:00.298103Z","state":"measured"},{"denominator":55,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":55,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2506.10269/citation-record","integrity":"/paper/2506.10269/integrity","json":"/paper/2506.10269/citation-record.json","paper":"/paper/2506.10269"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:38:01.441764Z","title":"Strong Mixed-Integer Programming Formulations for Trained Neural Networks.Mathematical Programming, 183(1):3–39, 2020","venue":null,"work_id":"01907ee9-3e10-4384-8a78-5e12a1d2cf50","year":2020},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T04:37:59.932014Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:ae98e5ac1aaca818dcdceefbe297d32dc89a5da1bd9533ad6456de08d5e4c654","observation_id":"eb27ed11-024b-44b4-98af-766c11448e2e","resolution":{"observed_at":"2026-08-07T04:38:01.447393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.423803Z","title":null,"venue":null,"work_id":"a9f4d51c-3fe0-41d0-9732-d11d1522024d","year":2025},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T04:37:59.938436Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:a82bda9cd18ceca19b3a27cb15fcbd15c23b1d8fc3c65cfc325a0ad68c9a80af","observation_id":"8c0f085f-840f-4910-b18d-a1b73968456f","resolution":{"observed_at":"2026-08-07T04:38:01.429771Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1409.0473","last_updated":"2016-05-19T21:53:22Z","snapshot_observed_at":"2026-07-06T03:53:10.336430Z","submitted_at":"2014-09-01T16:33:02Z","title":"Neural Machine Translation by Jointly Learning to Align and Translate","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.0473","snapshot_observed_at":"2026-08-07T04:37:59.943361Z","title":"Neural Machine Translation by Jointly Learning to Align and Translate.arXiv Preprint arXiv:1409.0473, 2014","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T04:37:59.943361Z"},"links":{"cited_paper":"/paper/1409.0473","citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:bdc814e8f971d0a5e29e0a5d57b20f5eb9269a0d2678d1c5f950ad4c87798a32","observation_id":"2b2b3b5d-00b1-42d2-b5be-8cae81bbd1fb","resolution":{"observed_at":"2026-08-07T04:37:59.943361Z","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":"2026-08-07T04:38:01.407238Z","title":"Measuring Neural Net Robustness With Constraints.Advances in Neural Information Processing Systems, 29, 2016","venue":null,"work_id":"5fc2791b-1d9e-438c-97dd-4c2038c33a09","year":2016},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T04:37:59.949187Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:1ffa6dd7b22cc3207e2d5f47af9bfc9a6ca515fdc15f80b3bdd88089c515f1f9","observation_id":"9f9cab6f-c874-4be6-aad9-648f52b4b491","resolution":{"observed_at":"2026-08-07T04:38:01.413029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.387397Z","title":"Efficient Neural Network Verification via Layer-Based Semidefinite Relaxations and Linear Cuts","venue":null,"work_id":"1ac74732-eef8-46f6-98f5-667c3ca76c63","year":2021},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T04:37:59.954248Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:5564f7f75ff78a2555ae815bd42fdc7c410d993e9aa5afffb3172a8b45b936fc","observation_id":"0c0d51ee-f3f2-420a-b96e-8655132d794d","resolution":{"observed_at":"2026-08-07T04:38:01.395094Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.368675Z","title":"Efficient Verification of ReLU-Based Neural Networks via Dependency Analysis","venue":null,"work_id":"d9f304fc-9e83-4dfd-85c5-bd8afbef5b73","year":2020},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T04:37:59.959663Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:e36e7259c1779f0780cd1ebd770b3b9948299f11f3647c682d23cfd829520deb","observation_id":"4205f471-b8b4-47ee-86d3-b822546de9fd","resolution":{"observed_at":"2026-08-07T04:38:01.373582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.353295Z","title":"Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers.Foundations and Trends® in Machine Learning, 3(1):1–122, 2011","venue":null,"work_id":"d1b15415-872b-425c-a05f-1b2808987d76","year":2011},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T04:37:59.966053Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:198d6f89bbfe9f088e903a69d8df6ea8effa0b0a1b9408735f276fdff385013b","observation_id":"efdf2190-10a7-456b-ab2d-a10f81e865ca","resolution":{"observed_at":"2026-08-07T04:38:01.358349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19985","last_updated":"2024-12-28T03:07:00Z","snapshot_observed_at":"2026-07-06T20:13:58.813488Z","submitted_at":"2024-12-28T03:07:00Z","title":"The Fifth International Verification of Neural Networks Competition (VNN-COMP 2024): Summary and Results","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.19985","snapshot_observed_at":"2026-08-07T04:37:59.970837Z","title":"The Fifth International Verification of Neural Networks Competition (VNN-COMP 2024): Summary and Results.arXiv Preprint arXiv:2412.19985, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T04:37:59.970837Z"},"links":{"cited_paper":"/paper/2412.19985","citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:a9d55f720410053431b10b51b63ba0e7cf53b6a9f69886f61baa6ec551da2d93","observation_id":"a7caee1c-ab5a-4df4-89da-b7922f5f0070","resolution":{"observed_at":"2026-08-07T04:37:59.970837Z","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":"2026-08-07T04:38:01.337543Z","title":"A Unified View of Piecewise Linear Neural Network Verification.Advances in Neural Information Processing Systems, 31, 2018","venue":null,"work_id":"fb12e8a4-5292-4807-a4ed-c0d15313a518","year":2018},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T04:37:59.978342Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:fb336da194dc16921aa168ed014913083da8dca14fff6f67ffacdad42ea709c5","observation_id":"8922dc2c-e6ba-42cf-90c5-d11a82a823bb","resolution":{"observed_at":"2026-08-07T04:38:01.343035Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.315114Z","title":"End-to-End Autonomous Driving: Challenges and Frontiers.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024","venue":null,"work_id":"2b9ca90c-07c0-468c-b755-007ad4469647","year":2024},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T04:37:59.985076Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:a9699267ca168feb505a4d0dfcdac1bd306d2426452e889c4adaa16a907ed49b","observation_id":"23ce62de-79cf-4423-be84-30f1f2ef87c5","resolution":{"observed_at":"2026-08-07T04:38:01.321548Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.296629Z","title":"Maximum Resilience of Artificial Neural Networks","venue":null,"work_id":"e61c1379-02b0-4b6c-a64d-916796fe1738","year":2017},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T04:37:59.990285Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:133fd2a02dc0b0c0da8f2ba3f4967325946753dea15508d870f6a1f0e91c2b70","observation_id":"f24c578c-c827-411b-a41f-8a7f29d65758","resolution":{"observed_at":"2026-08-07T04:38:01.302720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.278944Z","title":"Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations","venue":null,"work_id":"13c82f46-a4aa-4ded-a4b5-daa858ad14f3","year":2023},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T04:37:59.995525Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:5f103408362f55da42c28d7a381a46abbfdfd7779ad32321b77016ba3d88491c","observation_id":"359f69a0-ab43-4caa-858c-ae5dcfc4ac9b","resolution":{"observed_at":"2026-08-07T04:38:01.284056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.261125Z","title":"Certified Adversarial Robustness via Randomized Smoothing","venue":null,"work_id":"39f5bee5-4ec3-49f5-ba25-f8802877c986","year":2019},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.000798Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:068515776f7593d5c6119065c0afd4493e589e8746e76a2a94603ae1ac133257","observation_id":"d31dd728-f8b3-4d0f-9bee-b8e1a48a32fc","resolution":{"observed_at":"2026-08-07T04:38:01.266672Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.236251Z","title":"Enabling Certification of Verification-Agnostic Networks via Memory-Efficient Semidefinite Programming.Advances in Neural Information Processing Systems, 33:5318–5331, 2020","venue":null,"work_id":"3046ebe9-7b9b-4c48-b959-ecac4231de62","year":2020},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.013142Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:859a31f7ab18b9c53086c0b75226b5dfbd832aee9617ef89313575f78d54e33a","observation_id":"742f1e58-fa4e-4153-8014-2d17e8b1a5aa","resolution":{"observed_at":"2026-08-07T04:38:01.243796Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.214952Z","title":"The MNIST Database of Handwritten Digit Images for Machine Learning Research.IEEE Signal Processing Magazine, 29(6):141–142, 2012","venue":null,"work_id":"4665b274-1ea2-4648-b880-818138352521","year":2012},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.020969Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:37367aaac30329f100c7f637594ce1330a10fa681fda3acd9f54becfff407fe5","observation_id":"a971e7f6-f969-47bf-9147-d45bc19c10a4","resolution":{"observed_at":"2026-08-07T04:38:01.221657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.187179Z","title":"Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks","venue":null,"work_id":"e04bbbc5-a19d-4eac-9dd1-e37bfedf6398","year":2017},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.033637Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:6a0bba0e37628a9cdf24da69aa2aa71fbf309ad6fb364c998a3fe5af9ac17953","observation_id":"6c7b0dd2-4b9d-4935-824c-7fc0e0e23e90","resolution":{"observed_at":"2026-08-07T04:38:01.193667Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15594","last_updated":"2024-11-05T21:38:35Z","snapshot_observed_at":"2026-07-06T17:07:48.292847Z","submitted_at":"2023-12-25T03:05:09Z","title":"Scalable Approximate Optimal Diagonal Preconditioning","version":2},"cited_work":{"arxiv_id":"2312.15594","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.15594","snapshot_observed_at":"2026-08-07T04:38:00.445228Z","title":"Scalable Approximate Optimal Diagonal Preconditioning","venue":"math.NA","work_id":"af0851b5-6d91-45ef-ad2f-0a81c881009d","year":2023},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.039861Z"},"links":{"cited_paper":"/paper/2312.15594","citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:e840d594c7aab3ce9a6b07c4b96dede58bff56dee8bbab4b3e2c3e8c46ea1862","observation_id":"c6e8a0f4-c70b-40bd-91e2-c461c998438c","resolution":{"observed_at":"2026-08-07T04:38:00.452826Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6572","last_updated":"2015-03-20T20:19:16Z","snapshot_observed_at":"2026-07-06T04:04:16.777653Z","submitted_at":"2014-12-20T01:17:12Z","title":"Explaining and Harnessing Adversarial Examples","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6572","snapshot_observed_at":"2026-08-07T04:38:00.048224Z","title":"Explaining and Harnessing Adversarial Examples","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.048224Z"},"links":{"cited_paper":"/paper/1412.6572","citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:24fb1cf228d3bec1815fc47caf23b56df2aa7024d46e05e2e0f5d37fb26ff8c7","observation_id":"b6e553df-87ac-4f75-9fd1-46bad7cac339","resolution":{"observed_at":"2026-08-07T04:38:00.048224Z","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":"2026-08-07T04:38:01.164196Z","title":"Efficient Neural Network Verification via Adaptive Refinement and Adversarial Search","venue":null,"work_id":"049662ed-68d7-495b-bcfa-643effe0e472","year":2020},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.058325Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:f28256904b50f45f9aaa48492c1886748d178e6c5be6fff9634bac355510a70f","observation_id":"7014157b-eece-44f6-83bc-fb1efbe6a534","resolution":{"observed_at":"2026-08-07T04:38:01.172088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.138032Z","title":"Cambridge University Press, Cambridge, England, 2 edition, Oct 2012","venue":null,"work_id":"754d5602-02aa-4106-9f90-fd368c67ced3","year":2012},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.066780Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:e8382942ba60aa0a2208e06fa40189244c362999d4a799a1aeba858645774603","observation_id":"d210fdf7-ac1c-465f-885e-ce98a381b7c2","resolution":{"observed_at":"2026-08-07T04:38:01.144423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.109098Z","title":"Facial Reduction for Symmetry Reduced Semidefinite and Doubly Nonnegative Programs.Mathematical Programming, 200(1):475–529, 2023","venue":null,"work_id":"08d5b72b-dd2b-4978-8942-ee59d18f86a2","year":2023},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.073274Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:909e834b20e378cd6a14fd19f42d11b5686c9797945e9c18e5407e0532e39641","observation_id":"c174aaf8-5b54-4e0f-91f2-4dd45ba878f6","resolution":{"observed_at":"2026-08-07T04:38:01.121389Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.083043Z","title":"Safety Verification of Deep Neural Networks","venue":null,"work_id":"e4735227-f454-4018-b022-dc5d2435ff5c","year":2017},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.082987Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:0af0a701514351d51690dae1c85b43adf63e34c40235773f6d8a16ae9cb48ddf","observation_id":"c36626f0-75e3-4888-9860-9719097ef45c","resolution":{"observed_at":"2026-08-07T04:38:01.089530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.059732Z","title":"Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks","venue":null,"work_id":"a4649a74-83f2-4dcf-88a9-46bbc9cee5d3","year":2017},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.095131Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:48c7f4e9270a91948471ee19ceb3bfd2b9c474ba70a6411fe2cccff8ed8a166a","observation_id":"caa7b2e8-4212-45cc-ae7e-99b185c070c8","resolution":{"observed_at":"2026-08-07T04:38:01.065828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.040868Z","title":"Reluplex: A Calculus for Reasoning About Deep Neural Networks.Formal Methods in System Design, 60(1):87–116, 2022","venue":null,"work_id":"3af4bbf2-a359-4d70-a166-8f21ebd01841","year":2022},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.102814Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:455cdde93d97fe8cdbff0c0bb77d5a0b6e3d7a403972b38183cec09dd90636fe","observation_id":"93212bfb-4f0a-4a6f-b848-ba7fc20a5d54","resolution":{"observed_at":"2026-08-07T04:38:01.046938Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:01.018500Z","title":"ImageNet Classification With Deep Convolutional Neural Networks.Advances in Neural Information Processing Systems, 25, 2012","venue":null,"work_id":"cea877ab-78c1-468b-92f3-81533b1aeccd","year":2012},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.109065Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:ae3187fae85bce710676ee96cd974b77e1b20f3a104016301485f9f118b6ec19","observation_id":"2df4720a-bf95-4ded-99bf-546790fea349","resolution":{"observed_at":"2026-08-07T04:38:01.027303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.997510Z","title":"A Semidefinite Relaxation Based Branch-and-Bound Method for Tight Neural Network Verification","venue":null,"work_id":"52edb5ce-4733-434b-a865-f06d51fe2c86","year":2023},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.117594Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:d1fe6abb2dd86e9f9524a84f544511ffc2e829a985b6ea84bc97a88aeffc4d8a","observation_id":"65bb556a-69e2-4117-8c8c-c2d26fb767e0","resolution":{"observed_at":"2026-08-07T04:38:01.004526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.972335Z","title":"World Scientific, 2009","venue":null,"work_id":"337a9a18-45fb-4b1a-ae9f-37fe2f6ef4d7","year":2009},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.126179Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:89981d6bbdc9d2c02bd48bc0eeb3d42fbb0e835c874a8378d2d7ea25317855a8","observation_id":"ebf4718c-cf66-4537-a47b-47604d9e1cc7","resolution":{"observed_at":"2026-08-07T04:38:00.980311Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.953880Z","title":"SoK: Certified Robustness for Deep Neural Networks","venue":null,"work_id":"5191f2f0-b4cd-4f95-9253-a363804aaf2b","year":2023},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.130875Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:dc02af777d298e4ab1e5acde17b89359898d3b274b71b01fd8334519a6deac01","observation_id":"b01fb00d-d5d1-49ca-97a0-258b87244836","resolution":{"observed_at":"2026-08-07T04:38:00.959173Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.936887Z","title":"An ADMM-Based Interior-Point Method for Large-Scale Linear Programming.Optimization Methods and Software, 36(2-3):389–424, 2021","venue":null,"work_id":"d676098c-8fa3-4962-81b8-02ad25921d4f","year":2021},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.136504Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:4bf4f1429225db413730072ae3604688b751069f8c64638428840f419fac538f","observation_id":"86d3e5c2-fcd1-4c3c-b8bc-acce2f3afcd2","resolution":{"observed_at":"2026-08-07T04:38:00.942608Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1706.07351","last_updated":"2017-06-22T14:59:49Z","snapshot_observed_at":"2026-07-06T05:48:00.958213Z","submitted_at":"2017-06-22T14:59:49Z","title":"An approach to reachability analysis for feed-forward ReLU neural networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.07351","snapshot_observed_at":"2026-08-07T04:38:00.143913Z","title":"An Approach to Reachability Analysis for Feed-Forward ReLU Neural Networks.arXiv Preprint arXiv:1706.07351, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.143913Z"},"links":{"cited_paper":"/paper/1706.07351","citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:b9b5ac6492c94ad9dd6fb81e35dfeca46945b2030bc199199a8eb0f79ab4942e","observation_id":"cbfcaa1f-abaa-4462-a3a9-60d6d0990fb8","resolution":{"observed_at":"2026-08-07T04:38:00.143913Z","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":"2026-08-07T04:38:00.907419Z","title":"A Structural Geometrical Analysis of Weakly Infeasible SDPs.Journal of the Operations Research Society of Japan, 59(3):241–257, 2016","venue":null,"work_id":"3af870e6-72be-4a72-a980-a12627d07035","year":2016},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.152073Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:dfd87446698fb7d25ac109c18c9d69bfcb2d5a55902d2cda15c11873f2bd863d","observation_id":"e9fa1202-0b32-4441-8240-78730385353c","resolution":{"observed_at":"2026-08-07T04:38:00.920270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.886720Z","title":"Towards Deep Learning Models Resistant to Adversarial Attacks.International Conference on Learning Representations, 2018","venue":null,"work_id":"83f9d483-0854-4a0e-a3c2-480dd7c96e75","year":2018},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.158667Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:85b516925940374463249dc4491bcaf7cce1bb1f3c0b5bbc6a65677fc7b78b57","observation_id":"90aaa070-9ef6-42d4-84dd-4df349a5eff2","resolution":{"observed_at":"2026-08-07T04:38:00.893309Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.866801Z","title":"A Numerical Evaluation of Highly Accurate Multiple-Precision Arithmetic Version of Semidefinite Programming Solver: SDPA-GMP, -QD and -DD","venue":null,"work_id":"b6dafc2e-2532-4941-a896-f0bfa9c939c5","year":2010},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.165272Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:3ffa20788b2c85f459e63ffa802ce4c4215d793f31ee0a509642e913ee1ea79a","observation_id":"07bc43bd-6766-420c-8712-d013f34b260d","resolution":{"observed_at":"2026-08-07T04:38:00.872218Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.849562Z","title":"California Institute of Technology, 2000","venue":null,"work_id":"2f20d0f0-de95-4c1b-aa9d-64a627a98694","year":2000},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.171250Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:57d32959146c8b5ffef6142b82262cddbaf4ca94e6e459e8553bd3e59918817a","observation_id":"dad83c6d-ae6b-485a-9304-c9beeea7b372","resolution":{"observed_at":"2026-08-07T04:38:00.854971Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.831543Z","title":"Partial Facial Reduction: Simplified, Equivalent SDPs via Approximations of the PSD Cone.Mathematical Programming, 171:1–54, 2018","venue":null,"work_id":"1822d1dd-ce8e-4711-8927-2776f461a930","year":2018},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.177214Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:f3f813b6f697f8a6e4eb19f44bb9196611169dfbf061f6ebfe820a5ef85aa635","observation_id":"d2cff32e-1fe0-4085-bef1-850259bec8cd","resolution":{"observed_at":"2026-08-07T04:38:00.837184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.816213Z","title":"Semidefinite Relaxations for Certifying Robustness to Adversarial Examples.Advances in Neural Information Processing Systems, 31, 2018","venue":null,"work_id":"12ca1e74-a877-4d0f-a4ef-d2a320b372a5","year":2018},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.184892Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:5c4abbaa3afb2a69c60f86b570bcdc519d5502f290891691997f2c99dc8ea502","observation_id":"0cf1a5f8-a0e8-40fc-9be4-e5dca83a7489","resolution":{"observed_at":"2026-08-07T04:38:00.821142Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.798687Z","title":"A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks.Advances in Neural Information Processing Systems, 32, 2019","venue":null,"work_id":"7b359852-13fb-4cc5-888b-afb3f91c05bd","year":2019},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.189678Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:d6e5a92e2b55b2694c6a0bc25b3e32533080984cfe6bb1699b58a155e13b4e45","observation_id":"9fddd7e1-a345-4186-ae4d-7a845a920c67","resolution":{"observed_at":"2026-08-07T04:38:00.804123Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.777527Z","title":"Perturbation Analysis of Singular Semidefinite Programs and Its Applica- tions to Control Problems.Journal of Optimization Theory and Applications, 188:52–72, 2021","venue":null,"work_id":"2afac9f4-b9ca-4cb7-8a70-f88ddb2c340c","year":2021},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.195769Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:9f8fc77a70f13849abcd5cf95b094bbc570ce953c038624e9a116a88d16dcf69","observation_id":"e6d0ab6f-5082-4e2d-a785-e4f24b783be5","resolution":{"observed_at":"2026-08-07T04:38:00.786259Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.756117Z","title":"An Abstract Domain for Certifying Neural Networks.Proceedings of the ACM on Programming Languages, 3(POPL):1–30, 2019","venue":null,"work_id":"5af72e29-c651-4c63-9107-4830921e34c2","year":2019},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.201176Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:31b7c99e40f6792527c7b3f24e8a50e642072f6f70f70b88c45af1ccc7606f78","observation_id":"69866369-8374-4de4-ab8f-aa23b8823ed4","resolution":{"observed_at":"2026-08-07T04:38:00.763559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.732156Z","title":"SDPNAL+: A MATLAB Software for Semidefinite Programming With Bound Constraints (Version 1.0).Optimization Methods and Software, 35(1):87– 115, 2020","venue":null,"work_id":"00dddce5-1ad7-49f7-adce-4b13906a9ceb","year":2020},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.207091Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:798a6506b387fb7f436f21db57f771aa301b360fc33ab34a5c7055c0f505bbcb","observation_id":"7f806c7a-7ed9-4751-8475-9ebb571273f1","resolution":{"observed_at":"2026-08-07T04:38:00.739295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.714977Z","title":"Intriguing Properties of Neural Networks","venue":null,"work_id":"38eafc06-df55-4c49-b396-2b91939ce0cf","year":2014},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.214780Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:4b17255accb172574ef724e32382eb44c8b9ee26754b3bc9ae05ba31e414247e","observation_id":"bebeeade-e7f3-48a8-9d6a-332c9fd7a3b7","resolution":{"observed_at":"2026-08-07T04:38:00.720651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.07356","last_updated":"2019-02-18T04:39:10Z","snapshot_observed_at":"2026-07-06T06:10:21.255556Z","submitted_at":"2017-11-20T15:05:33Z","title":"Evaluating Robustness of Neural Networks with Mixed Integer Programming","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.07356","snapshot_observed_at":"2026-08-07T04:38:00.222117Z","title":"Evaluating Robustness of Neural Networks With Mixed Integer Programming.arXiv Preprint arXiv:1711.07356, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.222117Z"},"links":{"cited_paper":"/paper/1711.07356","citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:a11478e848c73447cbf7ecc6c5853951ef839e9f1877749f9aae53d5353e086f","observation_id":"daa68dd5-2cc1-4f84-b4e2-40b133d3c69f","resolution":{"observed_at":"2026-08-07T04:38:00.222117Z","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":"2026-08-07T04:38:00.696700Z","title":"Practical First-Order Methods for Large-Scale Semidefinite Programming","venue":null,"work_id":"5632693d-36ea-4174-9b7a-1dc8f74a9e04","year":2014},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.228631Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:c1b08db5db7892faa1cd7232b3b2eafff545eb4bc1b7ff6e09c6a1c22ca3edad","observation_id":"8d74474e-6849-43d1-b860-0b4e905dcc41","resolution":{"observed_at":"2026-08-07T04:38:00.702933Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.679273Z","title":"Facial Reduction Algorithms for Conic Optimization Problems.Journal of Optimization Theory and Applications, 158:188–215, 2013","venue":null,"work_id":"64276ba5-d693-4006-bda6-fec00156b24a","year":2013},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.236685Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:53e22d4209b2a0db267ab3648e22599e3e429f0f3c62031c4b884138c755d9dd","observation_id":"abb6b4cd-6727-4786-95da-51ceead8cc43","resolution":{"observed_at":"2026-08-07T04:38:00.684453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.662898Z","title":"Efficient Formal Safety Analysis of Neural Networks.Advances in Neural Information Processing Systems, 31, 2018","venue":null,"work_id":"86a12685-d293-4710-b3c4-541b46697c6c","year":2018},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.242151Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:01b382925d5bff1bfb66335546c43cbb6b0f352e1aa7f2142fc96d30bfaf63de","observation_id":"a56511a0-64c5-4a03-b37b-e3e262412d8e","resolution":{"observed_at":"2026-08-07T04:38:00.667989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.646638Z","title":"Beta-CROWN: Efficient Bound Propagation With Per-Neuron Split Constraints for Neural Network Robustness Verification","venue":null,"work_id":"c5a0c86f-138d-4a11-b390-f8ab099c2195","year":2021},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.247423Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:5e211e7eb32ca34e294f6df6d928515f2fd32b9ab3e8dfeb65ae913d10f7e812","observation_id":"c1a7724e-aa3a-4d1b-a44b-25f36d40093d","resolution":{"observed_at":"2026-08-07T04:38:00.651601Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.630825Z","title":"Towards Fast Computation of Certified Robustness for ReLU Networks","venue":null,"work_id":"ea3bcd75-19cb-443a-b03a-8379aa1b0618","year":2018},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.252809Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:2fc383745e066b4097f14a61d9d0a564b32b08bf0d840b39dcdc50bf713ed353","observation_id":"38a9f8b8-1e5f-44a8-9839-4da428399301","resolution":{"observed_at":"2026-08-07T04:38:00.636178Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.612925Z","title":"Provable Defenses Against Adversarial Examples via the Convex Outer Adversarial Polytope","venue":null,"work_id":"53ac4464-a9a6-4145-b257-726d3466a056","year":2018},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.257956Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:d46fb68cf66c3ea9b0ff420b3d24712fc7893194e9a4feacfa26c91d3357ad8a","observation_id":"bc37be23-195d-4d0a-894c-7fd31672b835","resolution":{"observed_at":"2026-08-07T04:38:00.619068Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.594503Z","title":"Numerical Optimization, 2006","venue":null,"work_id":"9339cf1d-ceab-4603-8aae-d7c62fd3b38e","year":2006},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.263277Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:8260c2ac0932cffe8d40ffa8d58fef5a739b8694632cb7dd21ebf2e8622e9ebc","observation_id":"44446fd4-c8c0-4e6b-a896-34bcc00491bb","resolution":{"observed_at":"2026-08-07T04:38:00.599369Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1708.07747","last_updated":"2017-09-15T21:29:49Z","snapshot_observed_at":"2026-07-06T05:56:41.814255Z","submitted_at":"2017-08-25T14:01:29Z","title":"Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.07747","snapshot_observed_at":"2026-08-07T04:38:00.267928Z","title":"Fashion-MNIST: A Novel Image Dataset for Benchmarking Machine Learning Algorithms.arXiv Preprint arXiv:1708.07747, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.267928Z"},"links":{"cited_paper":"/paper/1708.07747","citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:45752aee5b7e0053762f8f6311f6f5ee07b9a09c1c12b9f483a1a025cd0cb9e5","observation_id":"ddb6873e-face-4d86-b577-30d337af9707","resolution":{"observed_at":"2026-08-07T04:38:00.267928Z","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":"2026-08-07T04:38:00.574336Z","title":"Fast and Com- plete: Enabling Complete Neural Network Verification With Rapid and Massively Parallel Incomplete Verifiers","venue":null,"work_id":"cb44c2f0-5196-42a7-93c7-7f12f8674d76","year":2022},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.272962Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:8cc237449e23d412f4644e33ecd3af5bf7aef9d9b06a57d5d05d05aed1b812d3","observation_id":"648ed773-874d-4e6c-9811-6d5ee88a4fe7","resolution":{"observed_at":"2026-08-07T04:38:00.580924Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.556653Z","title":"Latest Developments in the SDPA Family for Solving Large-Scale SDPs.Handbook on Semidefinite, Conic and Polynomial Optimization, pages 687–713, 2012","venue":null,"work_id":"b5732533-bc4d-47c7-821d-de34da845c32","year":2012},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.278289Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:425678a98bf5643c152eff8a3ee92b230d0b11485442bddf3db60216f18ea052","observation_id":"19e61ad7-dc06-461e-bc1a-9a7974ce323a","resolution":{"observed_at":"2026-08-07T04:38:00.561946Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T04:38:00.534830Z","title":"A High-Performance Software Package for Semidefinite Programs: SDPA 7.Handbook on Semidefinite, Conic and Polynomial Optimization, 2010","venue":null,"work_id":"3451e49b-a8a8-4e65-ab11-ffcb799b89e3","year":2010},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.283633Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:527e864b8a088a1f00efb63110d1e84e533ed41499ba5b8311f8880402a2330e","observation_id":"648fa9d3-d246-4973-95d0-bf743b94fde4","resolution":{"observed_at":"2026-08-07T04:38:00.540530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1212.5701","last_updated":"2012-12-22T15:46:49Z","snapshot_observed_at":"2026-07-06T03:02:42.105044Z","submitted_at":"2012-12-22T15:46:49Z","title":"ADADELTA: An Adaptive Learning Rate Method","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1212.5701","snapshot_observed_at":"2026-08-07T04:38:00.290137Z","title":"ADADELTA: an Adaptive Learning Rate Method.arXiv preprint arXiv:1212.5701, 2012","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.290137Z"},"links":{"cited_paper":"/paper/1212.5701","citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:866e8c2bbfd8d3a4fa71d21ec81b780ce7146fe2aa91fb79cc6b5a2f62cdfe81","observation_id":"5c618eda-7e14-40c1-8bdf-c1f59411fde4","resolution":{"observed_at":"2026-08-07T04:38:00.290137Z","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":"2026-08-07T04:38:00.506450Z","title":"Scalable Neural Network Verification With Branch-and-Bound Inferred Cutting Planes.Advances in Neural Information Processing Systems, 2024","venue":null,"work_id":"47090c25-7ee2-4c81-9533-ac60b2ba56c7","year":2024},"citing_paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T04:38:00.298103Z"},"links":{"citing_paper":"/paper/2506.10269"},"observation_digest":"sha256:f52d0878121bc47005290743cc1711ac51d1875ea3fe465bd7036eeee26bf2a4","observation_id":"9bfe577f-c022-4008-8869-d1118f3500fe","resolution":{"observed_at":"2026-08-07T04:38:00.513620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.10269","last_updated":"2025-06-12T01:25:21Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T07:26:19.457541Z","submitted_at":"2025-06-12T01:25:21Z","title":"Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification"},"reference_resolution":{"displayed":55,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":1,"verified_fuzzy":46},"total_outbound_references":55},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2506.10269."}