{"as_of":"2026-08-24T01:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4f7dae2a4ef18317e294295623bde0fce585043d19a816e3bceb3dbcfc832c35","coverage":[{"denominator":90,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":90,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T14:02:43.437802Z","state":"measured"},{"denominator":90,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":90,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+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/2501.15767/citation-record","integrity":"/paper/2501.15767/integrity","json":"/paper/2501.15767/citation-record.json","paper":"/paper/2501.15767"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:02:43.166664Z","title":"Introduction to the numerical solution of markov chains","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.166664Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:2f31e3ff0fca87b120000068a1817fbaebfc1b5f886583568549a779f576be0f","observation_id":"8201d8fd-fedd-4640-bac3-d10fd0f05dca","resolution":{"observed_at":"2026-08-10T14:02:43.166664Z","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":"2026-08-10T14:02:43.170744Z","title":"Principles of model checking","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.170744Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:4415ed6271c14818a403eca4e757958fbcae2d3b2bbed951444a0d19712ddba2","observation_id":"1b5cf276-6dc3-4d17-8e17-0e8bd11bf2db","resolution":{"observed_at":"2026-08-10T14:02:43.170744Z","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":"2026-08-10T14:02:43.174040Z","title":"System reliability theory: models, statistical methods, and applications, volume 396","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.174040Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:bb945ebc36c30a59c71ff7e55a2a8a653493af0e6de6a7a21581574d4372dc59","observation_id":"15158d3a-a68d-42f8-a3c3-8b9f2725cef6","resolution":{"observed_at":"2026-08-10T14:02:43.174040Z","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":"2026-08-10T14:02:43.178095Z","title":"Markov models in medical decision making: a practical guide","venue":null,"work_id":null,"year":1993},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.178095Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:7da7db22406c8efd155fdf2e4c2ba597745ccbe0b0fdceaa7e1083d62e71c98d","observation_id":"1bf5dd55-46f2-4d0a-82e6-2bfa387f8071","resolution":{"observed_at":"2026-08-10T14:02:43.178095Z","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":"2026-08-10T14:02:43.181711Z","title":"Microsimulation modeling in food policy: A scoping review of methodological aspects","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.181711Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:6fbcfb6ffb6249ec9bf2804766f7b11598e72c3eb8e8e848046f69c8670daa8d","observation_id":"3af93f05-3296-4cfa-a364-db7a2280e08f","resolution":{"observed_at":"2026-08-10T14:02:43.181711Z","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":"2026-08-10T14:02:43.185136Z","title":"Microsimulation modeling for health decision sciences using r: a tutorial","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.185136Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:7e00eb569db5eac1036e292ca94072d6e4191e3612c9873d650bb1d6a86024fe","observation_id":"1af8f203-18df-49f4-b40a-c4e582907c70","resolution":{"observed_at":"2026-08-10T14:02:43.185136Z","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":"2026-08-10T14:02:43.188681Z","title":"A logic for reasoning about time and reliability","venue":null,"work_id":null,"year":1994},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.188681Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:1ace83b775216323c6c46012e86c2874e3d80a5a437ab3ae987ea18e6b1ac07d","observation_id":"3588f6fd-fac6-4df5-981d-b74f26695152","resolution":{"observed_at":"2026-08-10T14:02:43.188681Z","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":"2026-08-10T14:02:43.191913Z","title":"Prism: Probabilistic symbolic model checker","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.191913Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:1b715e307183bd7b7992ff74ba70425bdcaeb500d585dae8c73a9aaf65493115","observation_id":"48e779d7-79d0-4753-a9fd-c480d9a6aa0a","resolution":{"observed_at":"2026-08-10T14:02:43.191913Z","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":"2026-08-10T14:02:43.194929Z","title":"A markov reward model checker","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.194929Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:d9a0e2dace44334fecbe3460c330322d49f550265620e3c09b6cf76b9c92c3c4","observation_id":"7e7e3db7-ef22-4320-84b6-c81a4172f5ff","resolution":{"observed_at":"2026-08-10T14:02:43.194929Z","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":"2026-08-10T14:02:43.198258Z","title":"A markov chain model checker","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.198258Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:2ed4ae64e31cd0093d74372667983d45cf6044bd1a5dee601db00d77db34648d","observation_id":"ba56f39f-f06d-4763-b25e-30ce76d633f2","resolution":{"observed_at":"2026-08-10T14:02:43.198258Z","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":"2026-08-10T14:02:44.268761Z","title":"On statistical model checking of stochastic systems","venue":null,"work_id":"8b52f71b-cd59-41f1-9e0c-544e14f92576","year":2005},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.201412Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:5ea676ddc5c7a17f4306905cd9779f4500ba913ffe7b64dd8a0dc536fc96a52c","observation_id":"6a8f5ce7-3a4f-4d79-b3e0-ddfca19a2139","resolution":{"observed_at":"2026-08-10T14:02:44.272192Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.259942Z","title":"Ymer: A statistical model checker","venue":null,"work_id":"16ac7fe1-31a0-4801-9f3b-0f3f93b5883e","year":2005},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.204877Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:86aaea17faebe89fb1fdba08f242133cae7797cbaa12383b193cd533e41cfcd2","observation_id":"a9a4fdfb-7ce5-4382-ac14-e4a061b18a49","resolution":{"observed_at":"2026-08-10T14:02:44.262881Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.251268Z","title":"Approximate verification of probabilistic systems","venue":null,"work_id":"70b7ef6a-ec65-45e4-904f-16099b4cc592","year":2002},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.208027Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:096392302a3d052e263e0f3d0b0bed5776abca09b61631f5430201d691497f81","observation_id":"a1c29f43-1036-4135-bb9d-1c599e56c8bd","resolution":{"observed_at":"2026-08-10T14:02:44.254368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.242909Z","title":"Model-checking markov chains in the presence of uncertainties","venue":null,"work_id":"18174908-56d7-43d4-85c8-3000915790cf","year":2006},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.210654Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:3dcb18ab061da2ce2486f549e32d7abc711c32f822b5fa4c624defe9f92b79b2","observation_id":"f5bf2455-35c4-4491-b870-71da00db17df","resolution":{"observed_at":"2026-08-10T14:02:44.246145Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.233959Z","title":"Parameter synthesis for parametric interval markov chains","venue":null,"work_id":"ecdda591-464f-4c31-aa8a-5aa7a689685b","year":2015},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.213392Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:324796fb2bed241846d3252d73eb2295e8e1f32b011261cd664b0fdf70a4dcae","observation_id":"cb2cf192-2a54-4406-ab90-7d1e38a8f06a","resolution":{"observed_at":"2026-08-10T14:02:44.237502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.226146Z","title":"Parameter synthesis algorithms for parametric interval markov chains","venue":null,"work_id":"72d866a2-ea4f-4548-a755-7113f5f4f89e","year":2018},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.216166Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:77a586a7a00794731de88c6c139fa4235c5eefaa383bee734613812f32e59774","observation_id":"132cce75-bb2e-4778-bff6-8818df015ce3","resolution":{"observed_at":"2026-08-10T14:02:44.228821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.218198Z","title":"Model repair for markov decision processes","venue":null,"work_id":"9de2d9a1-3975-4567-ae06-1aa5db83f982","year":2013},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.218775Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:d5236ec4b6a32c945318a67025ab94fc7ce5c7af0db1e2f2424197eee66639a3","observation_id":"c7b99215-cada-442a-9ec2-e9491ca59bbf","resolution":{"observed_at":"2026-08-10T14:02:44.220885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.207681Z","title":"Parameter synthesis in Markov models","venue":null,"work_id":"e80c243a-ece6-4975-8f16-d5cc1a59a807","year":2020},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.221528Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:fb951d5e8777ec1192692f49c39de2e1273e1140df2306191f14a7f3b292e21f","observation_id":"9bd17b50-35b1-41e8-bef0-0392c591b27f","resolution":{"observed_at":"2026-08-10T14:02:44.210623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.199952Z","title":"Parameter synthesis for markov models: covering the parameter space","venue":null,"work_id":"52194f7f-0f72-4b81-b340-80a6ea73c900","year":2024},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.224509Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:b9cac3879d507ed0d4f7c837a5ac825cac95a0618a51b774e092e1cde391c265","observation_id":"3b4c08b7-32b3-4ef8-a0b8-4cdb22766ab7","resolution":{"observed_at":"2026-08-10T14:02:44.202624Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.191016Z","title":"Efficient sensitivity analysis for parametric robust markov chains","venue":null,"work_id":"7696da85-9920-40cf-969d-ed7d9fad4096","year":2023},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.227304Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:abfc10d2f137962d5e4f26246791ff2a2a3fe246c7e7066fcff3e74f241c5ccd","observation_id":"0a6b5211-a0cc-4a20-bdaa-f317ac208c14","resolution":{"observed_at":"2026-08-10T14:02:44.194233Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.182925Z","title":"On markov chains with uncertain data","venue":null,"work_id":"13cffd44-5312-4676-8372-caf50ef5b4f2","year":2008},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.229904Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:575fd528363c415a0cc43018fea4861d79275864b754a2d05511c0d129225f71","observation_id":"dcde74a9-c044-4899-8a49-2d7674de2e5a","resolution":{"observed_at":"2026-08-10T14:02:44.185913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1408.2029","last_updated":"2014-08-09T05:22:05Z","snapshot_observed_at":"2026-08-14T23:23:43.450450Z","submitted_at":"2014-08-09T05:22:05Z","title":"Sensitivity analysis for finite Markov chains in discrete time","version":1},"cited_work":{"arxiv_id":"1408.2029","doi":null,"metadata_source":"pith","pith_arxiv_id":"1408.2029","snapshot_observed_at":"2026-08-10T14:02:43.504849Z","title":"Sensitivity analysis for finite Markov chains in discrete time","venue":"cs.AI","work_id":"9535bc02-7678-4fdb-9cf3-39402338a0d2","year":2014},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.232494Z"},"links":{"cited_paper":"/paper/1408.2029","citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:86f0563ea2a847db5a9f3fb4315f8e0465e6fc04b3e2ef272fc877268bd56fca","observation_id":"8ad99ea3-ac3c-4539-a3b5-8906ac9226f8","resolution":{"observed_at":"2026-08-10T14:02:43.508247Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.174556Z","title":"Simulation-based optimization of markov reward processes","venue":null,"work_id":"d1b3871a-b0f9-4ac9-90e7-698baeccbcf3","year":2001},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.235464Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:d57106c9e2e4a4ef7a2290b5205bbb304c0523c3a7f32014305dd7c99b706c21","observation_id":"fdc17629-2961-4186-b71f-4dc1ba796d80","resolution":{"observed_at":"2026-08-10T14:02:44.177331Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.165458Z","title":"Approximate gradient methods in policy-space optimiza- tion of markov reward processes","venue":null,"work_id":"e475baed-8e92-4f54-b1bf-e922e7511712","year":2003},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.238319Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:533e53eb20728459779b90cd4b9d30c0c4af7bf854cd2f05eac4429d0e63bf36","observation_id":"73ec67b4-e374-4b75-b8ec-09d5e7b3c896","resolution":{"observed_at":"2026-08-10T14:02:44.169292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.156114Z","title":"Robust solutions to markov decision problems with uncertain transition matrices","venue":null,"work_id":"b4e20754-9acb-460d-81f7-17a6be6641df","year":2005},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.240996Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:02422aec001c2e11f5b532e42f8bba39dfb4582b65517a336dbfd0d2597288a4","observation_id":"7d49588e-d056-4c7b-b79d-4c06a853e55b","resolution":{"observed_at":"2026-08-10T14:02:44.159780Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.146813Z","title":"Robust dynamic programming","venue":null,"work_id":"7e313e9b-62fa-466a-a255-c8e21cba77ef","year":2005},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.243853Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:70162f08a23cd67b7fefec8f8770ad742ce866f4b36b6b7b4163b93ab54e4e14","observation_id":"0d339a75-8470-49ff-bc68-e2e603950129","resolution":{"observed_at":"2026-08-10T14:02:44.149701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.137296Z","title":"Robust markov decision processes: Beyond rectangu- larity","venue":null,"work_id":"db936022-45db-4f37-ab75-679115bf2beb","year":2023},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.246638Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:6910c43c9fc0aa49d84e34180f61f4b474fb3602f54148cda25a6e0b424f4c7a","observation_id":"5bfda0ef-c437-4a1e-9a0a-d696f65c5bc9","resolution":{"observed_at":"2026-08-10T14:02:44.140490Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.129081Z","title":"On the convex formulations of robust markov decision processes","venue":null,"work_id":"8b957009-c1ac-44ab-a57d-e6a7270e7d5f","year":2024},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.250024Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:1066dca8911f9b33674f0d87a508c4d228eb077188e0789b617872d9cdcf9a72","observation_id":"5a3dc358-e068-4091-9366-87a912b59c68","resolution":{"observed_at":"2026-08-10T14:02:44.132003Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.120396Z","title":"Data un- certainty in markov chains: Application to cost-effectiveness analyses of medical innovations","venue":null,"work_id":"8eb00c97-6dc5-4b90-9b02-8987c89d3ec2","year":2018},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.252746Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:352c04ea8d4fedf1c3b447f2f4c39bedaca244309363bc42c7093f2e45fc5eeb","observation_id":"25f1ca03-74f2-4d1d-94fd-a29926979822","resolution":{"observed_at":"2026-08-10T14:02:44.123576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.05471","last_updated":"2024-10-07T20:08:02Z","snapshot_observed_at":"2026-08-22T00:27:00.351147Z","submitted_at":"2024-10-07T20:08:02Z","title":"Exact sensitivity analysis of Markov reward processes via algebraic geometry","version":1},"cited_work":{"arxiv_id":"2410.05471","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.05471","snapshot_observed_at":"2026-08-10T14:02:43.492121Z","title":"Exact sensitivity analysis of Markov reward processes via algebraic geometry","venue":"math.OC","work_id":"196b59ec-df93-4eb4-bc9d-290a5f2b698e","year":2024},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.255491Z"},"links":{"cited_paper":"/paper/2410.05471","citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:acd68ffdff22a564a4c08b98c92c188479c37aa72aecd9c922468ff5b068cb27","observation_id":"2e31de81-aa64-43e8-9f07-cd6df2fa7167","resolution":{"observed_at":"2026-08-10T14:02:43.495632Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.112397Z","title":"ACAS Xu: Integrated collision avoidance and detect and avoid capability for uas","venue":null,"work_id":"0c764be3-85c7-4714-bb1a-e4e6110e288c","year":2019},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.258932Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:938f913ef6b259fb91fc3bad2e1d48f99852b80d10e7aa33bbe77e6fd7a92b81","observation_id":"f847397d-4d74-4c1c-b4b3-59e52797dbb0","resolution":{"observed_at":"2026-08-10T14:02:44.115225Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.104574Z","title":"Reluplex: An efficient smt solver for verifying deep neural networks","venue":null,"work_id":"eedec94c-8a7e-40ac-b6f5-7246cf0a4814","year":2017},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.261766Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:a7420f5124741010617e72955bc72ec225bb608a0cf29610ba41e1b48c130a19","observation_id":"185c0eca-2040-47fb-a0ea-0168ef22ab69","resolution":{"observed_at":"2026-08-10T14:02:44.107313Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.07356","last_updated":"2019-02-18T04:39:10Z","snapshot_observed_at":"2026-08-17T22:18:35.161858Z","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":"2026-08-10T14:02:43.264666Z","title":"Evaluating robustness of neural networks with mixed integer programming","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.264666Z"},"links":{"cited_paper":"/paper/1711.07356","citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:7f3b7525b40a6f7c8ef5499213d66f918f609aa574c78e21cecbcda32525a32a","observation_id":"64281409-da2e-4c0d-8299-3807029dda0f","resolution":{"observed_at":"2026-08-10T14:02:43.264666Z","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":"2026-08-10T14:02:44.095914Z","title":"Maximum resilience of artificial neural networks","venue":null,"work_id":"e1a0a75d-8173-4704-a1ba-dc2dde71493d","year":2017},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.267898Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:6e29ef3c9652df963182e7b4f4990f927fe469a7bec6ef84e47d0fb6f67783b2","observation_id":"f969c5b7-1bb6-41b5-bac3-31217ba5192b","resolution":{"observed_at":"2026-08-10T14:02:44.099384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.086770Z","title":"Strong mixed-integer programming formulations for trained neural networks","venue":null,"work_id":"ca027f2a-92d3-4dfc-a1f7-08ae92afefe9","year":2020},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.270584Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:7ce5c7f3a0778d39e6c118393087a57b8c87352881a15dfe8f1d372b3e03dd41","observation_id":"5b081c8e-316d-4319-a5b5-c3fb02744206","resolution":{"observed_at":"2026-08-10T14:02:44.090202Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.077269Z","title":"The convex relaxation barrier, revisited: Tightened single-neuron relaxations for neural network verification","venue":null,"work_id":"8ebfade4-e884-4582-be39-fe703a25fbed","year":2020},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.273609Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:9b7db3e67f35054176fcdc71cb73a97e8cf8ab3a5b00df6707fa4fc8761733b4","observation_id":"3867b272-bae4-432f-8075-7f802202ec3d","resolution":{"observed_at":"2026-08-10T14:02:44.080728Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.067248Z","title":"Between steps: Intermediate relaxations between big-m and convex hull formulations","venue":null,"work_id":"950665bf-c4b1-4e1c-8cad-4b46f652cda2","year":2021},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.276234Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:8b404ac820a34c98d75c7b35d615986bc75be9e0c5e705c27fd69f22aaf94d16","observation_id":"1fc4379e-4d48-45ca-8aa8-9209b84cef86","resolution":{"observed_at":"2026-08-10T14:02:44.070788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.14706","last_updated":"2022-11-27T03:25:48Z","snapshot_observed_at":"2026-08-16T16:13:05.580921Z","submitted_at":"2022-11-27T03:25:48Z","title":"Neural Network Verification as Piecewise Linear Optimization: Formulations for the Composition of Staircase Functions","version":1},"cited_work":{"arxiv_id":"2211.14706","doi":null,"metadata_source":"pith","pith_arxiv_id":"2211.14706","snapshot_observed_at":"2026-08-10T14:02:43.467403Z","title":"Neural Network Verification as Piecewise Linear Optimization: Formulations for the Composition of Staircase Functions","venue":"cs.LG","work_id":"f5c3aa17-aaad-4d58-a63b-265d9f372a97","year":2022},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.278978Z"},"links":{"cited_paper":"/paper/2211.14706","citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:d7908872422d6ffd6029fc3c5c462791e2a856a8d5d7db0e8b4deb16b8d41a5c","observation_id":"7199af1f-26c6-445c-a125-652ba8e8e48f","resolution":{"observed_at":"2026-08-10T14:02:43.472618Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.058044Z","title":"Beta-CROWN: Efficient bound propagation with per-neuron split constraints for complete and incomplete neural network verification","venue":null,"work_id":"851d13d1-13b8-47cd-aa80-07090c207114","year":2021},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.282499Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:391901691ad82b523130b7e96b57920bd27977bac69714d225bb77206ebb2386","observation_id":"6ff79e19-20ec-4171-96ee-3a87f1943414","resolution":{"observed_at":"2026-08-10T14:02:44.061440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.048774Z","title":"A branch and bound framework for stronger adversarial attacks of ReLU networks","venue":null,"work_id":"7d30b0c9-c4e5-4899-a165-c4e4400502a1","year":2022},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.285814Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:82a53b6482bcb3e5475b62074622e4a83fe46c76d3309e4f43af9ce781328d3e","observation_id":"54da0e60-cb43-4674-a29b-fee613dcb515","resolution":{"observed_at":"2026-08-10T14:02:44.052138Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.039785Z","title":"General cutting planes for bound-propagation-based neural network verification","venue":null,"work_id":"88dafd3f-3e4c-49d9-a34b-78ae74cbf6ea","year":2022},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.288880Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:eddebfab56b72ea0a7ffcd313423e2c9afec2ee81e53a246751d8056945473e8","observation_id":"100cc60c-3269-43c3-909c-bb66362915a1","resolution":{"observed_at":"2026-08-10T14:02:44.042817Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.029840Z","title":"Zico Kolter, Krishnamurthy Dvijotham, and Huan Zhang","venue":null,"work_id":"4dc7ef29-2cf0-4b85-87ac-afe73d8741df","year":2023},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.292007Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:ffb01f3fc3d1a69922818d30bf05f540312402d464402d7b27de382225e8da1c","observation_id":"6d2ec248-61ec-464f-ad08-44fa6bcc2aea","resolution":{"observed_at":"2026-08-10T14:02:44.033073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.019981Z","title":"Cost-effectiveness of a us national sugar-sweetened beverage tax with a multistakeholder approach: who pays and who benefits","venue":null,"work_id":"a600133e-4d7a-4098-aba0-e72851f41516","year":2019},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.295257Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:8851d9c07f8f4e004260885e00c4b69791f54f0cd3ca4eb803c6c42250ffccfe","observation_id":"187206bd-aed5-4797-93f3-4bca923bf275","resolution":{"observed_at":"2026-08-10T14:02:44.023540Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.011221Z","title":"Health impact and cost- effectiveness of volume, tiered, and absolute sugar content sugar-sweetened beverage tax policies in the united states: a microsimulation study","venue":null,"work_id":"14a27750-3c6f-4447-b5f0-01d2ac474ba3","year":2020},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.298698Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:cbdf009e73c2ac854384d4215539affdcb3601ab2ef8190de6d6826abd079c5e","observation_id":"83477604-8c8d-447f-b497-1b4b1e497808","resolution":{"observed_at":"2026-08-10T14:02:44.014285Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:44.002470Z","title":"Cost-effectiveness of population-based, community, workplace and individual policies for diabetes prevention in the uk","venue":null,"work_id":"3b246b1c-4ea5-4eb9-80d6-183c31000154","year":2017},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.301978Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:29c729e7b6ee4c60319bf69573b39649ce6dc362c22a3ea65d1a2309427aa1b0","observation_id":"f7941c20-1799-4023-bd0d-3bc0e8a46fe0","resolution":{"observed_at":"2026-08-10T14:02:44.005708Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.993402Z","title":"Handbook of global optimization, volume 2","venue":null,"work_id":"78499545-3879-4cca-9c36-d161b76596a9","year":2013},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.305066Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:c7a57c6eb498ad99fd37e6547f6cd010e312bec5a6cfe1e1f559424b95550de3","observation_id":"8ab37077-e8e4-4005-b4c0-bb5d5f651bc3","resolution":{"observed_at":"2026-08-10T14:02:43.996358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.984985Z","title":"Computability of global solutions to factorable nonconvex programs: Part i—convex underestimating problems","venue":null,"work_id":"67c1fd01-a47d-40d5-9841-f6353f0926b5","year":1976},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.308301Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:e3c6599de71681153556d133f3912f6bd37108a20e4184a5b2f126d1b5a2ad9c","observation_id":"cbcf7d5f-9d75-4168-90b1-311d7b5434bb","resolution":{"observed_at":"2026-08-10T14:02:43.987945Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:02:43.311661Z","title":"Gurobi Optimizer Reference Manual, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.311661Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:1626ffc81e41f90a9a7ef880f9d32c3ad60675cc9e7c93f72d92840c1df94c06","observation_id":"cd944047-bdf3-465c-95b1-d43383d93da4","resolution":{"observed_at":"2026-08-10T14:02:43.311661Z","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":"2026-08-10T14:02:43.971664Z","title":"New socp relaxation and branching rule for bipartite bilinear programs","venue":null,"work_id":"6c5288f9-76c2-4fdc-b04f-840b584a435b","year":2019},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.314972Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:eae6ca00e11ad69b1ad13035377ef5afe4f13808c8cf78c5a8ccf62cf9ad3cbb","observation_id":"c0d45515-ee86-4dc3-9abc-1cced9b6a23c","resolution":{"observed_at":"2026-08-10T14:02:43.974604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:02:43.317810Z","title":"Markov decision processes: discrete stochastic dynamic programming","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.317810Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:b8b6cf0b283c76a63e99e55e143f394521d479c4f8b68f1df23746b8d9f81478","observation_id":"ab3e2053-7ad4-4204-a6a4-2d392c251db1","resolution":{"observed_at":"2026-08-10T14:02:43.317810Z","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":"2026-08-10T14:02:43.957748Z","title":"Mathematical theory of reliability","venue":null,"work_id":"c2043512-6743-42cb-b5ad-f8b4e8e0c83a","year":1996},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.320282Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:eaa06f88b58a082aebe44c4ea3b024400d99c3f8f46fa654577b31f15bf7de94","observation_id":"e852aec6-8b13-4d93-9387-32cae0a05e9f","resolution":{"observed_at":"2026-08-10T14:02:43.960501Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.947893Z","title":"Determining the acceptance of cadaveric livers using an implicit model of the waiting list","venue":null,"work_id":"fc76f93f-a8bf-4c84-abb9-64b5415c8dbc","year":2007},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.323270Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:712c966bb68a7c6c432adc4b03863f31057ae1aadd45708ae2f685333b1956a8","observation_id":"ae7af8a8-338b-47a4-afe9-e5de7d7b74cc","resolution":{"observed_at":"2026-08-10T14:02:43.951558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.826580Z","title":null,"venue":null,"work_id":"25887ab4-9a82-481a-97d2-061e71868c8c","year":1984},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.326440Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:f72e3c641993b1a574e287746f40958fc37209eceaf4c8956ba24135e4866880","observation_id":"5dafcb24-9875-41c8-847d-2d8e691028a9","resolution":{"observed_at":"2026-08-10T14:02:43.941323Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.816725Z","title":"New techniques for the analysis of linear interval equations","venue":null,"work_id":"4b5926d4-8989-4d79-876e-c3b16643df27","year":1984},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.329431Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:eac08ee907462d08672abd85025626cf527a2c2fbea2c672cda229e39ef3e1c2","observation_id":"2a0c7c8e-2984-487c-b1a3-3af3238037ee","resolution":{"observed_at":"2026-08-10T14:02:43.820309Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:02:43.332247Z","title":"Nonnegative matrices in the mathematical sciences","venue":null,"work_id":null,"year":1994},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.332247Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:5911cc193222895e577a5c9f421adb75aed2a96cf228ff9eb51b08dee2c8cbcf","observation_id":"c5dee3b6-d055-48ae-a1ef-24135b9be849","resolution":{"observed_at":"2026-08-10T14:02:43.332247Z","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":"2026-08-10T14:02:43.334945Z","title":"Pedregosa, G","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.334945Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:7db39fc1f560e6678385d61c23796f296f525a26ca87a67493ac9f9c98e1e757","observation_id":"ac413ce3-2e3f-47f1-aca6-9e3d29868703","resolution":{"observed_at":"2026-08-10T14:02:43.334945Z","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":"2026-08-10T14:02:43.337899Z","title":"Pytorch: An imperative style, high-performance deep learning library","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.337899Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:4ab1b71d8de8068aa424748c0940d2cd76079415092c0f92a2b4c6cc8b907f2a","observation_id":"05055ca7-cc02-41c6-b999-3771ed3fb6ec","resolution":{"observed_at":"2026-08-10T14:02:43.337899Z","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":"2026-08-10T14:02:43.791366Z","title":"Gurobi machine learning, 2024","venue":null,"work_id":"bd813389-44f8-4bf2-abfe-5272b7ab0379","year":2024},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.340753Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:4abbf4d4afcfec6ed270971191a3f0f8617f85af7c48c8540f57c05401f5f7aa","observation_id":"7b62b66a-61f4-4218-b7c6-ab693bd40c39","resolution":{"observed_at":"2026-08-10T14:02:43.794755Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.782252Z","title":"Cost-effectiveness of drone-delivered automated external defibrillators for cardiac arrest","venue":null,"work_id":"6197d547-6fd5-4716-b4a5-5eccfcf81660","year":2025},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.343404Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:c5653d7ab50dff371dd0ffc26335d1971151be2581da7e4071eea589dab5bd44","observation_id":"024c3e63-64e1-4c3d-92c5-5624721359ed","resolution":{"observed_at":"2026-08-10T14:02:43.785444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.773040Z","title":"Association between sex and mortality in adults with in-hospital and out-of-hospital cardiac arrest: A systematic review and meta-analysis","venue":null,"work_id":"351e9268-7696-47d3-8fd2-94037a796b95","year":2020},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.346531Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:f36bb7b7d09763a2e59c9495ecc228f127ba6fd2bc0e0661d3fd30c3328872ff","observation_id":"b1add0d8-800a-4983-89a8-f2eb90f448bd","resolution":{"observed_at":"2026-08-10T14:02:43.776418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.764022Z","title":"Interval linear and nonlinear systems","venue":null,"work_id":"5dc75c93-839f-474d-933e-f0379c6ab119","year":2019},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.349357Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:11856806469ab0118376b17cfa9bb4a9d2212e7a5e1ee3eefdaf822ef350b477","observation_id":"d0b6addf-9a10-4420-b8d8-ea5dcc38b9c8","resolution":{"observed_at":"2026-08-10T14:02:43.767597Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.755906Z","title":null,"venue":null,"work_id":"dc18656c-bde7-48e9-8f15-3a13fc1a5bab","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.352611Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:1e00bd94ceb6c9ef3528fc2645e5ee8ac6a6ce25ae5870ac5424a310a41959c9","observation_id":"d756afdf-3dfd-468e-ac25-ec13c265139d","resolution":{"observed_at":"2026-08-10T14:02:43.758624Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.747407Z","title":null,"venue":null,"work_id":"32a0102e-113e-459d-8bc7-9e3bba09f25f","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.355678Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:75bd803dba40e48bb937121c86fd02aa643caa4177b092a5de022fba9da1cc8c","observation_id":"2ce9ba08-3882-488c-8f20-2748dbaeb95c","resolution":{"observed_at":"2026-08-10T14:02:43.750310Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.739163Z","title":"All operations above are interval arithmetic operations","venue":null,"work_id":"2b16bf01-57f6-41b9-8414-df65ac7eeefd","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.358489Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:9fe9b7fe6216c924cdc611a31b8ea5e3555ebecc62640a4f78d201596b743166","observation_id":"5fc12d66-d9ef-4376-98b0-0d9b2a43e4ca","resolution":{"observed_at":"2026-08-10T14:02:43.742055Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.731448Z","title":null,"venue":null,"work_id":"1df30fb6-ccb1-4a14-a422-8a10e2c809ea","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.361466Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:8d4c6369c693c847dbdcddbea9372c9d27620ecf8b44fde8af70e7c304131146","observation_id":"93d6e3b0-b6fb-4274-b33a-bd3a727b68f4","resolution":{"observed_at":"2026-08-10T14:02:43.734186Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.723175Z","title":null,"venue":null,"work_id":"fabd0473-a7d8-4905-9f5f-c14d20080cab","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.364134Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:e86e6816a638e2ec3c954360506fd107d725d3ec4b8fe809c480eee4952feb59","observation_id":"42ec2b94-9b55-4d6c-9707-cbec80f8dfa7","resolution":{"observed_at":"2026-08-10T14:02:43.726215Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.715006Z","title":null,"venue":null,"work_id":"4a52517a-2e22-4ddb-b22b-07b489348873","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.366982Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:59947c116d12efd690862bd78d99a5b5e041e2b002fbdaaa4157a5fb71c651c0","observation_id":"034c95ca-a75e-48ef-8903-10284807d94d","resolution":{"observed_at":"2026-08-10T14:02:43.717752Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.706743Z","title":null,"venue":null,"work_id":"1ef6b3e3-34ed-468a-a672-f69fe70d026f","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.370574Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:f3933ee93902c252a805669ae21291c17e34abbfb7f867661b0dd711f05d8d4b","observation_id":"b6814bb7-6471-41a3-a60d-3ba625617b64","resolution":{"observed_at":"2026-08-10T14:02:43.709643Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.697804Z","title":"if-then\" rules specified in natural language, e.g., “if age >= 65 then 0.8","venue":null,"work_id":"778faa15-1792-4956-8682-5cbc4c90fe5e","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.373369Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:43784c866391718b0023c8de74ccd5b7577baa5bda7e95db0dc0b79b05ef5158","observation_id":"f51bf02b-727a-42e0-8b23-11b1bb8f9117","resolution":{"observed_at":"2026-08-10T14:02:43.701026Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.689074Z","title":null,"venue":null,"work_id":"a8765d29-49bd-4b66-acf4-cb980ff291f7","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.376371Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:0800613f0d60259f53c8809bf8498e95f96e347f4b43760f27dcb6d152b226a8","observation_id":"905cd0f0-f1c5-4d44-8cfb-2fb7736724a4","resolution":{"observed_at":"2026-08-10T14:02:43.692201Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.680319Z","title":"Models for r and π are always used, while the number of modeled rows in P varies from 1 to 19, so that the total number of models runs from 3 to 21","venue":null,"work_id":"75536834-7009-4f86-b2ba-8537db8e220d","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.379424Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:21463f8c4e3fc5daf31da1ee8d76b4618c81a6ebd8aea07c1b44e7bea91ecdaa","observation_id":"660d3bda-fcb5-4a79-9022-8c9e65998794","resolution":{"observed_at":"2026-08-10T14:02:43.683621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.670903Z","title":"Remaining rows of P are uniform","venue":null,"work_id":"6cf92e60-860a-49de-ae4b-39de3b955809","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.382343Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:305c1e4356cf605919598873db9af869478c0bb204cbf05889ba87eb230047a6","observation_id":"3318f39c-6f8e-4770-9409-f30cf6c5c05c","resolution":{"observed_at":"2026-08-10T14:02:43.674145Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.661348Z","title":"We vary hidden layers in {1, 2} and neurons per layer in {5, 10, 15, 20}, with remaining rows of P set uniformly","venue":null,"work_id":"086a8205-b177-478d-9670-567cc2da2599","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.385337Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:0a6bf0fe772b8691e2a4560c761ddfee235b6c2cbbe1ad9efb86844656fa501b","observation_id":"c5898a8b-9a3f-4b4f-88b2-1f29c79b58e5","resolution":{"observed_at":"2026-08-10T14:02:43.664940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.653439Z","title":"[Yes] \" is generally preferable to","venue":null,"work_id":"a0368b71-9a34-4073-bc18-88ca062af8ae","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.388107Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:ff12306b994182b32844d380f21aa64a6fb71b5e62775005ebaa41403e6dd95a","observation_id":"bdd9fde8-7647-4301-a7d7-1add30f90133","resolution":{"observed_at":"2026-08-10T14:02:43.656254Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.644857Z","title":"Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper","venue":null,"work_id":"60fc661b-3073-4cae-a239-ecd3d501a52c","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.390890Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:04d3730e411b0b85c1b7706260ed032cf0298b96a77ce38136880134ee152c64","observation_id":"95c94d45-5951-409a-97fd-7b7a5525bc75","resolution":{"observed_at":"2026-08-10T14:02:43.648058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.637040Z","title":"Limitations","venue":null,"work_id":"55dadb79-5fac-4f64-bf08-4b1a1c40f22c","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.394147Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:abf930892f53d434662dbfecc6e066619f1b9beca2fad164302e52f86ffd05e9","observation_id":"eb3100b6-fbfd-4ed7-a2fb-9b0202b93432","resolution":{"observed_at":"2026-08-10T14:02:43.639887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.628894Z","title":"For proofs using more novel techniques (e.g","venue":null,"work_id":"b3d29fbd-9065-4cf6-a487-0084425273c3","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.397470Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:488b7b214ad8cbeec28a002f20cbd6838c30a1cdadb3d2e0d5967506062ce7b8","observation_id":"3af61c1d-cd70-430b-860d-3605036827a1","resolution":{"observed_at":"2026-08-10T14:02:43.631790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.621340Z","title":"As well, we release all code for the numerical experiments (with instructions on how to run each of the experiments with a simple command-line command)","venue":null,"work_id":"482023b3-d87f-4cee-a613-42ddda74fbd4","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.400714Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:6b1c44c336046e9289d1c89f1637147700a428936b459b3e262712a8bcf7595e","observation_id":"2b499f03-836c-4be1-a0c9-b24b853797b9","resolution":{"observed_at":"2026-08-10T14:02:43.624128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.613884Z","title":"We also release all the code for the numerical experiments, as simple scripts to run them, and for the case study","venue":null,"work_id":"c09f1d38-e669-4bcc-b91e-67b047f922e9","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.404119Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:e87ea2548a88db4d28eba14105fe4baea9399cb415e2a054513fd9e0973f1357","observation_id":"84e97058-9d6f-4392-b6de-a94a6c0af4df","resolution":{"observed_at":"2026-08-10T14:02:43.616685Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.606178Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"c48831cc-2402-44db-89d2-062a5d086349","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.407295Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:946094320889c574437f5f56591b6e023021f1159d4f45d11721ab6e0c49c3a7","observation_id":"d1491dbf-9047-42a8-a52d-730124684744","resolution":{"observed_at":"2026-08-10T14:02:43.608794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.598171Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"20bd99f9-8727-4c30-8119-4e9a72f41218","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.410538Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:8ee072a508e386ed446328d6c6783aa309b0af8e57e916fba8a7a1b687b3f031","observation_id":"db990547-59e1-462f-a528-81dea8cb1f63","resolution":{"observed_at":"2026-08-10T14:02:43.601022Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.590518Z","title":null,"venue":null,"work_id":"bcb3092a-55a1-4c41-97b7-f956074d93ba","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.414029Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:f4c24a775b64a62569191d68baec7b2e2d166c3d5ba823dd18250ffe72560a69","observation_id":"297037e5-44f3-428f-bc1b-1550e8bea5e1","resolution":{"observed_at":"2026-08-10T14:02:43.593255Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.580351Z","title":"Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics","venue":null,"work_id":"f546fae9-647e-475e-898c-944dd30030d6","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.417478Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:b201590086e87057262a0ab95118e7660bd83d7763dfbeb85c5f5bc917a8a661","observation_id":"32d09db7-5854-4fd6-9f85-61706b24cb09","resolution":{"observed_at":"2026-08-10T14:02:43.583650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.570776Z","title":"Guidelines: • The answer NA means that there is no societal impact of the work performed","venue":null,"work_id":"91aef80b-9157-48a0-bc60-12a4adc45e12","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.421025Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:3503d5b0f4124121c7881ec7b39fa3a25c2432d2f1ea4429ee0bc39c9cdc47d2","observation_id":"b652b833-dbe9-4c49-973c-3f28ef0c48ff","resolution":{"observed_at":"2026-08-10T14:02:43.574267Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.560818Z","title":"Guidelines: • The answer NA means that the paper poses no such risks","venue":null,"work_id":"5b6a2c8f-f5ce-471a-88af-fb8c1a20305a","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.424322Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:d54e4e49d12455f20dd4becec791e450ee3cfe11d5c86e34404a9687b29982b0","observation_id":"e3035af1-8a09-4e01-9081-bb88522ff879","resolution":{"observed_at":"2026-08-10T14:02:43.564533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.551318Z","title":"Guidelines: • The answer NA means that the paper does not use existing assets","venue":null,"work_id":"75e1bd4e-349c-4977-a62c-79e880408832","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.427049Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:03a968df253ef416e5013d8702cd4bc2f19a3da4535bed27153a25e26cd620f6","observation_id":"2ead9a7b-bf5f-4ef4-a7d3-c8c24e5be41c","resolution":{"observed_at":"2026-08-10T14:02:43.554836Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.542113Z","title":"Guidelines: • The answer NA means that the paper does not release new assets","venue":null,"work_id":"41b78eab-8f0a-4f61-9721-348d6a6301cb","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.429929Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:804548a18926c57b1d400f79b26f4d2f33d25ca6635f3e34c7cfe4c4b8260a18","observation_id":"e4016cb7-884b-4862-ae21-615066b09722","resolution":{"observed_at":"2026-08-10T14:02:43.545184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.532169Z","title":"Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects","venue":null,"work_id":"a36b4ec7-8c46-42b6-aa1c-0cc68e7622ae","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.432637Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:670ea67434808fadf791514b5d099079fbc832e37993889970c523066fbb35dc","observation_id":"7edca5fa-6385-4372-9e30-0ae44392ee3b","resolution":{"observed_at":"2026-08-10T14:02:43.535304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.523704Z","title":"Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects","venue":null,"work_id":"7b5bb1bf-2de5-4412-8e01-53dd2c9c3883","year":null},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.435262Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:e934a06f4ee04fa90dcd58272db5a2249ddaa990b157319ba0384907f29b6027","observation_id":"13d935ed-79d9-4976-a0ca-64aec68523c9","resolution":{"observed_at":"2026-08-10T14:02:43.526722Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T14:02:43.514464Z","title":"Answer: [No] Justification: Does not use LLMs","venue":null,"work_id":"a8fcd6fa-9f9a-42d3-971a-c7d3e64ed11d","year":2025},"citing_paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters","version":2},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-10T14:02:43.437802Z"},"links":{"citing_paper":"/paper/2501.15767"},"observation_digest":"sha256:8af98a66cc428cbdf92256fbf28e32d142db9328c7a3bd262da658b635f82b65","observation_id":"516a494f-904f-4977-8e3e-983740f762e3","resolution":{"observed_at":"2026-08-10T14:02:43.517886Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.15767","last_updated":"2025-05-11T08:04:44Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T02:46:39.972277Z","submitted_at":"2025-01-27T04:34:22Z","title":"Formal Verification of Markov Processes with Learned Parameters"},"reference_resolution":{"displayed":90,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":25,"verified_exact":3,"verified_fuzzy":62},"total_outbound_references":90},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 24 August 2026, this Paper Citation Record lists 90 of 90 outbound references and 0 inbound Pith citation observations for arXiv:2501.15767."}