{"as_of":"2026-08-18T13:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cae1c6fb5b00fac27b59e8abf74719b19d010f7ffba06ad1be212d6a23f781ab","coverage":[{"denominator":96,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":96,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T17:28:53.471180Z","state":"measured"},{"denominator":98,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":98,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T06:17:28.993762Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.10845","snapshot_observed_at":"2026-08-03T03:34:32.335203Z","title":"Bandfuzz: An ml-powered collaborative fuzzing framework, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.07666","last_updated":"2026-08-02T23:24:12Z","snapshot_observed_at":"2026-08-06T23:24:20.105607Z","submitted_at":"2026-02-07T19:21:27Z","title":"SoK: DARPA's AI Cyber Challenge (AIxCC): Competition Design, Architectures, and Lessons Learned","version":4},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-03T03:34:32.335203Z"},"links":{"cited_paper":"/paper/2507.10845","citing_paper":"/paper/2602.07666"},"observation_digest":"sha256:af10b2f51749e45f9289cb3304743e7ced529d8d6f6e5453a1ab4b90b9758f9a","observation_id":"4608654a-323e-48b7-8f74-d759e6173c0e","resolution":{"observed_at":"2026-08-03T03:34:32.335203Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.10845","snapshot_observed_at":"2026-08-04T06:17:28.993762Z","title":"Bandfuzz: An ml-powered collaborative fuzzing framework, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.07666","last_updated":"2026-08-02T23:24:12Z","snapshot_observed_at":"2026-08-06T23:24:20.105607Z","submitted_at":"2026-02-07T19:21:27Z","title":"SoK: DARPA's AI Cyber Challenge (AIxCC): Competition Design, Architectures, and Lessons Learned","version":5},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-04T06:17:28.993762Z"},"links":{"cited_paper":"/paper/2507.10845","citing_paper":"/paper/2602.07666"},"observation_digest":"sha256:4793ccd834f3e95a4519d5c0f51997506fa3683e8ebb029ff4be2e09604e85f3","observation_id":"1f78bac9-8b2a-49a3-b453-67c8b49223c8","resolution":{"observed_at":"2026-08-04T06:17:28.993762Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2507.10845/citation-record","integrity":"/paper/2507.10845/integrity","json":"/paper/2507.10845/citation-record.json","paper":"/paper/2507.10845"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:28:43.970423Z","title":"Neuzz: Efficient fuzzing with neural program smoothing,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:43.970423Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:c69be079d856d4acd7738acb64eb8f827a1ec86d04673f3b9ff520c6da975c75","observation_id":"ea76c1ed-f7b3-4582-9e26-2a339bb563a8","resolution":{"observed_at":"2026-08-06T17:28:43.970423Z","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":"2026-08-06T17:28:44.045014Z","title":"Mtfuzz: fuzzing with a multi-task neural network,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:44.045014Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:1918907e050aad2b967fdaa5349a2ef4727920fa3d5c7afeebcfa3b839848825","observation_id":"745dad12-8be1-4dc3-bd2c-7cef2edad53a","resolution":{"observed_at":"2026-08-06T17:28:44.045014Z","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":"2026-08-06T17:28:44.163555Z","title":"Cerebro: context-aware adaptive fuzzing for effective vulnerability detection,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:44.163555Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:83d68eb19d89884b98c899b9e433c25cdcbf75ef8e7a31faa803c50746da6cef","observation_id":"4ef9d26f-a93a-443f-a5d6-7302d60ac893","resolution":{"observed_at":"2026-08-06T17:28:44.163555Z","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":"2026-08-06T17:28:44.311349Z","title":"Not all coverage measurements are equal: Fuzzing by coverage accounting for input prioritization","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:44.311349Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:db14e2ba403243c5e9ecea647246976aea3c2e9e58f4aff5b68a4121e79d05da","observation_id":"049240b6-5d36-407c-9da0-907b8780eb12","resolution":{"observed_at":"2026-08-06T17:28:44.311349Z","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":"2026-08-06T17:28:44.407492Z","title":"Alphuzz: Monte carlo search on seed-mutation tree for coverage-guided fuzzing,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:44.407492Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:991bc1df0215af6dbf857391f1dee158515497e667b46a7d29b0ec80a5850133","observation_id":"a48fa42a-a959-4aab-a0f5-a79ef1b7ddf7","resolution":{"observed_at":"2026-08-06T17:28:44.407492Z","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":"2026-08-06T17:28:44.486935Z","title":"Reinforcement learning-based hierar- chical seed scheduling for greybox fuzzing,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:44.486935Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:ba600c6fe5f94e2ef61812ac26d2e997e12b1c39c9b2c0b3ed4c36798053e245","observation_id":"86354823-ecfa-45ca-9cc6-cbbc5216075e","resolution":{"observed_at":"2026-08-06T17:28:44.486935Z","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":"2026-08-06T17:28:44.554982Z","title":"Optimizing seed selection for fuzzing,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:44.554982Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:d8bd1b0e6b397198adcdeb96ce6a2a292d944b6d482d1d9f796119bfb53c6454","observation_id":"af91feff-1275-4668-b4ed-a8fa7e9176ae","resolution":{"observed_at":"2026-08-06T17:28:44.554982Z","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":"2026-08-06T17:28:44.642268Z","title":"Deepfuzzer: Accelerated deep greybox fuzzing,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:44.642268Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:190b615d77785310944ed44589e4a733168e31915bfd13f9241fa4b3e6203f20","observation_id":"a28401a7-65a9-4488-a5ae-94e01e19ee17","resolution":{"observed_at":"2026-08-06T17:28:44.642268Z","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":"2026-08-06T17:28:44.751177Z","title":"Seed selection for successful fuzzing,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:44.751177Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:1a4b01c384a266f082a83dec0d855979d8d3a460865bd4b0a26990c8a5db0574","observation_id":"c49785f2-f16f-484d-92ed-074e85a4160f","resolution":{"observed_at":"2026-08-06T17:28:44.751177Z","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":"2026-08-06T17:28:44.810362Z","title":"Collafl: Path sensitive fuzzing,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:44.810362Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:68f6d0ce036cdccdcb3912dce7377e2e3b4f9da29e69e53c1330e96877b7deff","observation_id":"b5683215-71ae-4733-9400-8c705ad4a989","resolution":{"observed_at":"2026-08-06T17:28:44.810362Z","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":"2026-08-06T17:28:45.027961Z","title":"Better pay attention whilst fuzzing,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:45.027961Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:7ac6384e40de43796382e34f78671909f75272376938df7dd204879d96e67c89","observation_id":"419c9a02-0082-4042-b370-1ec6f413e9bb","resolution":{"observed_at":"2026-08-06T17:28:45.027961Z","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":"2026-08-06T17:28:45.113071Z","title":"Coverage-based greybox fuzzing as markov chain,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:45.113071Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:96c495b9ce0406b02cdf9399262edfcf4d2adae76493e6b4bb43e46d7ff3b049","observation_id":"5e44fafa-5186-4b3c-be0c-7e0772775042","resolution":{"observed_at":"2026-08-06T17:28:45.113071Z","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":"2026-08-06T17:28:45.204270Z","title":"Ecofuzz: Adaptive energy-saving greybox fuzzing as a variant of the adversarial multi-armed bandit,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:45.204270Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:5e2d95c6dd10f19e3cd995b62d52a6e045879f4005c42f7d675e339d9264ce47","observation_id":"ed6264d0-a944-4fa3-812b-22afcace72d9","resolution":{"observed_at":"2026-08-06T17:28:45.204270Z","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":"2026-08-06T17:28:45.322460Z","title":"Vuzzer: Application-aware evolutionary fuzzing","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:45.322460Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:bf8e866eed6b4cbb4ab91814f026ae73092c5b3e66bf117a9fff38817e161114","observation_id":"f928cae3-93c1-4425-9f00-f37be4f246a3","resolution":{"observed_at":"2026-08-06T17:28:45.322460Z","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":"2026-08-06T17:28:45.418383Z","title":"Fairfuzz: A targeted mutation strategy for increasing greybox fuzz testing coverage,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:45.418383Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:19ae34cee515e042f80a608a40a5ccb9346ec1c1850e9d28b710e2d4f33873ce","observation_id":"022ac75e-7675-40d0-83a7-465762a2da3f","resolution":{"observed_at":"2026-08-06T17:28:45.418383Z","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":"2026-08-06T17:28:45.461545Z","title":"Darwin: Survival of the fittest fuzzing mutators,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:45.461545Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:e82d739486b0422fa726158206821201f0840d36e6095fe589f84ebfe84e545f","observation_id":"2da94f47-2828-40f8-9094-9e499c674bc8","resolution":{"observed_at":"2026-08-06T17:28:45.461545Z","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":"2026-08-06T17:29:04.115155Z","title":"Mopt: Optimized mutation scheduling for fuzzers,","venue":null,"work_id":"f9fce8f8-36e3-4d71-8e6a-f70263a5d0a6","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:45.573815Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:8b9879a7497e79c1a5c34d4381471931f67019c45b6149fe5ae00cc504498fcb","observation_id":"735fbf00-ec25-4edb-8dc3-333c7b3b1df1","resolution":{"observed_at":"2026-08-06T17:29:04.231695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:03.867060Z","title":"Redqueen: Fuzzing with input-to-state correspondence,","venue":null,"work_id":"817f121d-9dd0-4c3b-bd7f-7eacec094cb3","year":2019},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:45.652953Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:768519bf8a2f4ea92041433b73fb5327048dc750662847097bb4248d11b28990","observation_id":"a741b446-9b56-45d5-9fcf-324bf98d6519","resolution":{"observed_at":"2026-08-06T17:29:03.942945Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:03.563627Z","title":"Aki helin / radamsa · gitlab,","venue":null,"work_id":"023c77d8-2627-49ac-be78-2d4598721a48","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:45.738210Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:5732e0939624953ba22e5d4bc8e67f02cb21d0f0e539f1676d651f864be2c595","observation_id":"b8540690-fcfe-4fce-bb00-999977a38ae0","resolution":{"observed_at":"2026-08-06T17:29:03.740876Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:03.403311Z","title":"Profuzzer: On-the-fly input type probing for better zero- day vulnerability discovery,","venue":null,"work_id":"dbd1e9ca-b151-4087-8e04-d386aaa2eb95","year":2019},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:45.804776Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:21d3414d8a3525212c6f8b40fd526f9cc7d3082b99ec8a437a0cfc9b9c6dd571","observation_id":"f181f056-12fd-4a93-a719-a10ea24067d1","resolution":{"observed_at":"2026-08-06T17:29:03.493063Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:03.208991Z","title":"Cmfuzz: context- aware adaptive mutation for fuzzers,","venue":null,"work_id":"8ddcc0af-3cbf-46d3-afd7-b62d1aa200ea","year":2021},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:45.935107Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:aa5fdacc3960f8563635cd7fc154816b8e2ccf0cb25a6dd87828bd39465fe072","observation_id":"12971bca-b199-43c7-bfec-c115c7fbe633","resolution":{"observed_at":"2026-08-06T17:29:03.315803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:02.967741Z","title":"Learning seed-adaptive mutation strate- gies for greybox fuzzing,","venue":null,"work_id":"60a65b48-fb66-435e-bd33-bd1dfaba0348","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:46.031814Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:5eb39a82c2e1d3766df356ff98e226b654c8f775fbdea1f41b6d8a6a9d7be6c6","observation_id":"3ffe4e34-e1a9-4630-a1ba-8f5e15fc1345","resolution":{"observed_at":"2026-08-06T17:29:03.073415Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:02.684880Z","title":"Sok: Prudent evaluation practices for fuzzing,","venue":null,"work_id":"d153813c-08c5-4d2e-8ebe-7e83006afb2d","year":2024},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:46.080736Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:fa85639a0629f67b170eb2615ae5f4c7a410e9b02b40a305b0d6da3aa48bbedd","observation_id":"866c1d2f-888a-4f4b-9629-cceffdbcc817","resolution":{"observed_at":"2026-08-06T17:29:02.805654Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:02.450831Z","title":"Fuzzbench: 2023-12-15-aflpp report,","venue":null,"work_id":"828c272a-3c79-4adb-ab79-369b8750d569","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:46.205669Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:f5dddf12f166bc4dff93a1dd6371e66658131ec355ee1ae61261218c8287054d","observation_id":"5ad16ae9-3e0c-4c9b-bd55-ba996b02f606","resolution":{"observed_at":"2026-08-06T17:29:02.571453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:02.152866Z","title":"Sbft tool competition 2023–fuzzing track,","venue":null,"work_id":"282cff12-142c-4d58-8e6e-a467d389c180","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:46.387468Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:48f9ea1712d86ed998ea74b70dc7d5434659eeb5777adf05661f0c5365fc394a","observation_id":"98f40db3-e7f5-4720-878a-c3c2b93742a6","resolution":{"observed_at":"2026-08-06T17:29:02.277878Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:01.859925Z","title":"Afl++: Combining incremental steps of fuzzing research,","venue":null,"work_id":"18431cf6-f9df-4d52-87f1-53302e20811d","year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:46.489347Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:b5f449a5b9b0793675c5d2d95921fe2dd5f46f235e3dec2ab9567421d9162423","observation_id":"5065b6a6-3c26-4d76-8ca7-46ad751456af","resolution":{"observed_at":"2026-08-06T17:29:01.975154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:01.831129Z","title":"Fuzzbench reports,","venue":null,"work_id":"f8b68223-faca-4bbb-8d4b-799e2a282b3f","year":2024},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:46.583521Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:05bfa5e1fc1b13af7f94c193e88c974341237b56a4fc6ab90a0707f09faba60a","observation_id":"627b4a28-c6cd-40c8-8f35-dbf705a63248","resolution":{"observed_at":"2026-08-06T17:29:01.844062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:01.750493Z","title":"Sbft 2023 fuzzing competition,","venue":null,"work_id":"12dbde5b-ec6c-4216-8c14-628bad19b72d","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:46.693631Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:ce848bb8661eab49f861c046d916a5bb708459450144b63d8dcd125b73507a52","observation_id":"4433a9c7-1c31-4858-ad12-2f6b75d2aae3","resolution":{"observed_at":"2026-08-06T17:29:01.790278Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:01.660453Z","title":"Collabfuzz: A framework for collaborative fuzzing,","venue":null,"work_id":"d5f4e38f-1fb6-4637-a914-b11a6de03fca","year":2021},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:46.829533Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:71102ebb8780b1ab7204397f4af969f95f6046a0a43674f5e7221caa2c81fcb8","observation_id":"0a3d7c21-1367-4749-965c-901992b35723","resolution":{"observed_at":"2026-08-06T17:29:01.696369Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:01.495239Z","title":"Cupid: Automatic fuzzer selection for collaborative fuzzing,","venue":null,"work_id":"44f95c4a-4155-4b15-9088-68974f3f89b6","year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:46.960031Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:8034e67e70af103f944595ba225eadf68b8affd2ffc6efb96c87a2805fe70b0a","observation_id":"32910439-09d4-4ca8-9a11-811614117835","resolution":{"observed_at":"2026-08-06T17:29:01.587583Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:01.353794Z","title":"Enfuzz: Ensemble fuzzing with seed synchronization among diverse fuzzers,","venue":null,"work_id":"8103b80a-6415-4559-8c03-75221e9acbf7","year":2019},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:47.053185Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:04b49f30021edfd3d482f38f210154bc3574a7a66836eff9ac9d6e4884d0725f","observation_id":"de925b5c-5a23-4d95-8604-4f5913ccf3b2","resolution":{"observed_at":"2026-08-06T17:29:01.397010Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:01.222713Z","title":"autofz: Automated fuzzer composition at runtime,","venue":null,"work_id":"52a8532f-f3ab-44dc-a37f-b493817e2d7f","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:47.170799Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:92c7f49408211c7ab881b71b66398021e4a6210f8b18ed91e07504090ddc1130","observation_id":"b951c5d6-e3ef-4be5-a393-df2878510aee","resolution":{"observed_at":"2026-08-06T17:29:01.283372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:01.101357Z","title":"Fuzzbench: an open fuzzer benchmarking platform and service,","venue":null,"work_id":"d991f091-8392-40e6-b5ff-0a892a84c593","year":2021},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:47.277419Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:d497fe180f25e62a415152c8854482c71efe92e5f8695bd86cb06ea14fcbff1d","observation_id":"db9cbe4a-46f5-4345-a64b-b443a8f38848","resolution":{"observed_at":"2026-08-06T17:29:01.165019Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:00.975364Z","title":"Fuzzer test suite (fts),","venue":null,"work_id":"a3cc4c7a-0b3b-4898-8fc1-049f81fca8e4","year":2021},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:47.374997Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:365b3d729b808a4d7c37358e5b1fc348b9ed1f27ed4216c2533b184359d985e5","observation_id":"5a99959a-5802-46b9-b58c-805b06b5d569","resolution":{"observed_at":"2026-08-06T17:29:01.008477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:47.468896Z","title":"American fuzzy lop,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:47.468896Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:fe386a5df30a1861b39a546a406f01c4146b4f6dbe7cdaed431ae3bedf1b2aa9","observation_id":"e482c6e2-e041-4262-9447-0868529da13f","resolution":{"observed_at":"2026-08-06T17:28:47.468896Z","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":"2026-08-06T17:29:00.878653Z","title":"Angora: Efficient fuzzing by principled search,","venue":null,"work_id":"b5fda961-b80d-4267-a339-1d8b2f077ffb","year":2018},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:47.568792Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:9b5a477387384fe5e05ce8538cd7b6e348cb56446691e77d3287ede80ddb5c00","observation_id":"fcc610dc-c043-45d3-85c1-940dd63ed340","resolution":{"observed_at":"2026-08-06T17:29:00.921850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:00.796400Z","title":"Send hardest problems my way: Probabilistic path prioritization for hybrid fuzzing","venue":null,"work_id":"50e51eab-0d79-4254-8ef6-7509a55774ee","year":2019},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:47.694778Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:4f72eb993993638228d2b47b915e4b7289174a742c759690f7613899d3b24484","observation_id":"8758ab3a-7a1a-46c2-b36a-09534c411436","resolution":{"observed_at":"2026-08-06T17:29:00.827570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:00.691622Z","title":"Smart greybox fuzzing,","venue":null,"work_id":"65bafc1f-786c-4601-a0be-ec876e4050c8","year":2019},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:47.770113Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:ad903a45729d8927c3d3db2b1d6c3c5d798b2912acdce7ba7a85146f9107bb90","observation_id":"21df49bf-0782-4e83-b6ef-b8e2f5444b3d","resolution":{"observed_at":"2026-08-06T17:29:00.742408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:00.548461Z","title":"Path tran- sitions tell more: Optimizing fuzzing schedules via runtime program states,","venue":null,"work_id":"4c255bba-70db-45ab-8039-4742ea605e71","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:47.896337Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:ecff77342fc8675e98978d1ba928ca01c054b5396fd9edd4d38d283172453dda","observation_id":"b3df31b7-c242-4265-9b9f-17c59ae729d7","resolution":{"observed_at":"2026-08-06T17:29:00.609496Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:00.431869Z","title":"A novel coverage-guided greybox fuzzing based on power schedule optimization with time complexity,","venue":null,"work_id":"897d81ae-3793-4cf5-b596-b70473bce206","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:48.002371Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:111da0e0a0bc453fe54ae06b17c3d876a347a059bbba1947471863052423966b","observation_id":"4dcdf068-39c6-4287-9c48-9972da799951","resolution":{"observed_at":"2026-08-06T17:29:00.482189Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:00.319565Z","title":"Driller: Augmenting fuzzing through selective symbolic execution","venue":null,"work_id":"6c5fbe2b-1c41-45bd-a7b4-422565c033ba","year":2016},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:48.086921Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:f26f20ebcb2d579b28475e1f2ad5bdf1e98a9e8d8f4d089a18a58e9d12ead96e","observation_id":"a0ae8d21-f598-4dc4-8d32-9957a38d5062","resolution":{"observed_at":"2026-08-06T17:29:00.358721Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:00.197423Z","title":"Symsan: Time and space efficient concolic execution via dynamic data-flow analysis,","venue":null,"work_id":"a4433b2a-daf6-4ff5-973e-7811c71c560a","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:48.154265Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:75f82f733bf851c6bf954c373d2654517df30dff5990a143615703029d5b2a78","observation_id":"d68d6470-00e3-4008-95c9-544585492ba5","resolution":{"observed_at":"2026-08-06T17:29:00.262860Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:29:00.083028Z","title":"Symbolic execution with symcc: Don’t interpret, compile!","venue":null,"work_id":"47a4ceaf-bfea-42a4-89ed-663bca268af5","year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:48.280490Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:83b4dfd7d1f7ea71cc09c0f749b546010d8ad1e17feb54cfb4e3796832a5736b","observation_id":"466e47f8-2a42-45d2-a0c6-bd8ad39bdd9f","resolution":{"observed_at":"2026-08-06T17:29:00.135322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:59.961104Z","title":"Qsym: A practical concolic execution engine tailored for hybrid fuzzing,","venue":null,"work_id":"90eea509-1c59-49f5-b776-407a1948b889","year":2018},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:48.364836Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:4c610b0e8ef00a6c81120f12e7241424bcd12822639be158545b071352855c16","observation_id":"bd8e49d6-2a2d-4868-a3af-150a9f075b1b","resolution":{"observed_at":"2026-08-06T17:29:00.014109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:59.858106Z","title":"Symqemu: Compilation-based sym- bolic execution for binaries,","venue":null,"work_id":"03a5e2be-8677-4753-bdc8-543cb203cda1","year":2021},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:48.486004Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:5b215b2bb5ee88f4d1f002826fad3850a919d04ee80b3ed13a1bc4e796c64f0a","observation_id":"d8946c35-827d-4fa6-bf3e-a57a0e8b1cdc","resolution":{"observed_at":"2026-08-06T17:28:59.892187Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:59.735435Z","title":"Pangolin: Incre- mental hybrid fuzzing with polyhedral path abstraction,","venue":null,"work_id":"7fca5aa4-749c-4c9d-9098-f4ed6eb14e39","year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:48.576719Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:e4734e9797d098b299239cb8ac59f4907ec857acb81a27237ddca68c7b2d73c7","observation_id":"a757c115-d51b-4d7b-a857-1d838f2a035d","resolution":{"observed_at":"2026-08-06T17:28:59.789421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:59.603211Z","title":"Fuzzolic: mixing fuzzing and concolic execution,","venue":null,"work_id":"c281fcfd-2ac4-4d4a-8d69-0762286c2c78","year":2021},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:48.653369Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:00186aa6f3b2ea9b74e145d183ac9acfc42a05171d52b8bd830ce3e060efcbf2","observation_id":"5cd59a8a-0fac-43fd-8a8e-40a2d1e34ae5","resolution":{"observed_at":"2026-08-06T17:28:59.659842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:59.496540Z","title":"Drifuzz: Harvesting bugs in device drivers from golden seeds,","venue":null,"work_id":"e00f1d80-09e1-4f04-9058-12894579dd54","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:48.767410Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:18e3aea310bca7a4a9bc3d159144fc67374a7dbbafa094313fdb221f653411db","observation_id":"b034506e-2028-4ed2-b7cf-2f1230760271","resolution":{"observed_at":"2026-08-06T17:28:59.548667Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:59.361871Z","title":"Pata: Fuzzing with path aware taint analysis,","venue":null,"work_id":"28386ce5-ce5c-4f7f-be5c-34a046b859e9","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:48.862690Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:0dc979230dcbc796230ffd235b3485704046fc1f96080064bc541111b5b2c07e","observation_id":"bc609c94-c2a7-478f-81b4-368686bc96c4","resolution":{"observed_at":"2026-08-06T17:28:59.428651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:59.244582Z","title":"Greyone: Data flow sensitive fuzzing,","venue":null,"work_id":"91c5068d-7f98-4f7f-bf70-62054e4295ab","year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:48.927906Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:262004b6172b0afe145f44f7737e42ecf21d24dd072bbf8c40a91a141f99e2bc","observation_id":"a0b42d3e-6238-4c88-97c0-b50e614c3d21","resolution":{"observed_at":"2026-08-06T17:28:59.307865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:59.091688Z","title":"Hfl: Hybrid fuzzing on the linux kernel","venue":null,"work_id":"20e245e1-d808-4132-aeba-6f0e3ed6b1ef","year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:49.006026Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:926e95b11111ead9618e17aec6bab84afa7b839e3ebcb913e9ba82a2dc746d99","observation_id":"b5986edc-a017-42df-912c-ebaf71638112","resolution":{"observed_at":"2026-08-06T17:28:59.161951Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:58.968304Z","title":"Di- rected greybox fuzzing,","venue":null,"work_id":"f1c5bf80-a2d5-442d-b64b-0d711d71ef66","year":2017},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:49.088063Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:b912da3b152a63dd5b8c4103c7f023589ad6df849f8620ce51dce41442fa4f1f","observation_id":"a5afdc8f-bc08-4187-a6e7-9f2c217046ae","resolution":{"observed_at":"2026-08-06T17:28:59.002842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:58.872251Z","title":"Perffuzz: Automati- cally generating pathological inputs,","venue":null,"work_id":"c44472ee-d0a3-4925-82ca-26ab6e12dea4","year":2018},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:49.178753Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:2bccf9aeb1d7c22adc01b2e4feb2048c43c07c4ead9377c50be237d0e6036a53","observation_id":"7155e71e-60bf-4c65-8540-a7532fb839aa","resolution":{"observed_at":"2026-08-06T17:28:58.920625Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:58.739080Z","title":"Maxafl: Maximizing code coverage with a gradient-based optimization technique,","venue":null,"work_id":"af625d56-63c7-4f3a-b67a-2fccee4cc58f","year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:49.349099Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:9c4985f212bbaebe385f7eb13173cfa879650c90b183d7044ba7a875d418a840","observation_id":"699846f0-bf6f-4b68-9b19-749f0200bfee","resolution":{"observed_at":"2026-08-06T17:28:58.803000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:58.635666Z","title":"No free lunch theorems for op- timization,","venue":null,"work_id":"88243188-2a02-4643-96c1-595e7d0fd145","year":1997},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:49.472480Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:5026b19cf750af1675898f05fc25ad1aba9b6e9c0c0c47658d8359dcd19e52c7","observation_id":"d1f538f8-37d8-4c4f-8170-4d4ff885faf5","resolution":{"observed_at":"2026-08-06T17:28:58.687082Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:58.522582Z","title":"A tutorial on thompson sampling,","venue":null,"work_id":"6669b962-2d79-4a37-9c77-ad6a5d2d9417","year":2018},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:49.569936Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:1c090fd199a0bed3e03fb79316ade87b89a72109ca35e7c93ade18fc5b164dfb","observation_id":"fcc1d8cd-48f7-4c87-baf5-4fb5046d4555","resolution":{"observed_at":"2026-08-06T17:28:58.560420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:58.396789Z","title":"On the likelihood that one unknown probability exceeds another in view of the evidence of two samples,","venue":null,"work_id":"237ef83c-d61e-4e2e-abb9-44cab1d8051a","year":1933},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:49.660232Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:e95a10bf48e02c8c3b52e1ccdc98e11b940e129b66f1d5b1472753454edabf17","observation_id":"86b9d740-373e-46e7-985d-ab57c7496dfb","resolution":{"observed_at":"2026-08-06T17:28:58.455174Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:58.309056Z","title":"Matching in multi-arm bandit with collision,","venue":null,"work_id":"18f5a8fe-f9f8-4969-8f6f-27ad23227816","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:49.775937Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:07ff7c8e6a896ce5c407f9213742b2f0509142dc8d03d699a51849cab9df043d","observation_id":"479b1a85-740d-47f3-abae-27d17eba195f","resolution":{"observed_at":"2026-08-06T17:28:58.345981Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:58.161319Z","title":"Finite-time analysis of the multiarmed bandit problem,","venue":null,"work_id":"5fc91b7c-9927-4838-ad5b-18281cc129a6","year":2002},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:49.925752Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:9fb4482f7a9360297b5562369a9a868a6568ec9e6f836d81afb29890e8934d96","observation_id":"09d50870-e67c-4308-8317-603744eb35d0","resolution":{"observed_at":"2026-08-06T17:28:58.238160Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:58.054806Z","title":"An empirical evaluation of thompson sam- pling,","venue":null,"work_id":"24506b2f-ae80-4135-8a3a-d4d404c6d9d9","year":2011},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:49.991737Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:71c2d20213784ab717c4a3e8d7f9edcb96f46e30d5c1fbdb87a862a7a633b9ef","observation_id":"15e8a7f6-cac1-4a8d-a822-359dd593d797","resolution":{"observed_at":"2026-08-06T17:28:58.091526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:57.980777Z","title":"Analysis of thompson sampling for the multi-armed bandit problem,","venue":null,"work_id":"5d258fa5-52ac-4d09-bc46-01293ba54a24","year":2012},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:50.100171Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:eeb6eb7264717a224193d2e197e6a56199f22afa5553fcc7db2743410035a18b","observation_id":"46cf7781-8b27-407d-aaef-8da6b0000009","resolution":{"observed_at":"2026-08-06T17:28:58.019677Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:57.834262Z","title":"Honggfuzz: Security oriented software fuzzer,","venue":null,"work_id":"26e8f95a-9821-4508-96b7-78fa5fcc83fc","year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:50.257623Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:ec0d3b3c465837d21f9d1f3ef5a7167bea6620f51f94fcd3c3e9e23704add5ab","observation_id":"65ebb2c7-9cb8-4f01-a077-7bd83296b854","resolution":{"observed_at":"2026-08-06T17:28:57.900447Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:57.720610Z","title":"Laf-intel,","venue":null,"work_id":"21667bdd-e4f4-40fb-a581-d93b0e3e656c","year":2016},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:50.382520Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:78b218752e4e67ca76641213583e3ca90c7f5e93fac505d9e6c0934033819274","observation_id":"bad1757e-a37e-4004-9e2f-6f633fca9aaa","resolution":{"observed_at":"2026-08-06T17:28:57.773295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:57.593330Z","title":"Slime: program-sensitive energy allocation for fuzzing,","venue":null,"work_id":"41db29ee-f6a0-431f-86d2-f0aa360c5802","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:50.475130Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:cbe40a6bd1de146ed8a6e008c6e2e48ab13d1a702feb88bec2586dbc09759c85","observation_id":"9d50ff44-2057-46c0-a4b5-943e611dbded","resolution":{"observed_at":"2026-08-06T17:28:57.642616Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:57.479171Z","title":"Mobfuzz: Adaptive multi-objective optimization in gray-box fuzzing,","venue":null,"work_id":"d737d0b3-5258-48e4-b0ac-b4567865e82b","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:50.564540Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:3b1569dc973621d93dfba8ad066bb127691eb7528615678e3f4a6fe61ca3dff7","observation_id":"5f5cda0b-ed44-4dba-b9df-096b41735acd","resolution":{"observed_at":"2026-08-06T17:28:57.541246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:57.369893Z","title":"Fishfuzz: Catch deeper bugs by throwing larger nets,","venue":null,"work_id":"dfe47868-d185-4a94-b05f-e1836dca2946","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:50.693750Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:426855c2e99a66b60f58f0e56e1fa5c74c74b43fd01e9944a64e163d55c47c37","observation_id":"ce4ecf51-6834-4d94-85bf-4d28728bad00","resolution":{"observed_at":"2026-08-06T17:28:57.423818Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:57.193692Z","title":"Hollander, D","venue":null,"work_id":"a623ed58-82a3-4e41-a346-bc96464c062f","year":2013},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:50.777639Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:4884a3a9793d6e64adcf975c0386279ce73fe21d070379fbe5674d01038c62f2","observation_id":"78e8d984-11d6-4083-b77e-f958a97d999b","resolution":{"observed_at":"2026-08-06T17:28:57.308841Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:57.073758Z","title":"Sbft 2024 fuzzing competition,","venue":null,"work_id":"4191d771-9cbb-47d3-8fd9-2a4ed3922d91","year":2024},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:50.886278Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:bf8bbee6c59f602b01b7f21231f2c9109ed355a7d46b26e27cd5154667b8da1e","observation_id":"6b6b3456-9bbc-4837-b02a-e6010cc2e6b4","resolution":{"observed_at":"2026-08-06T17:28:57.122608Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:56.956191Z","title":"Systematic assessment of fuzzers using mutation anal- ysis,","venue":null,"work_id":"58d58e03-02f2-4249-a17e-b54d1ac16f12","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:51.027060Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:4bad5d7b4ef48becdff286c86a9eba57295b099d2f7f3754949b527e2ecebcff","observation_id":"8ea9dbe6-7fb6-4ef0-9492-53ff6a8120bb","resolution":{"observed_at":"2026-08-06T17:28:57.006828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:56.808403Z","title":"Libafl: A framework to build modular and reusable fuzzers,","venue":null,"work_id":"6e231301-d0e6-48a6-a10f-d7e63615155d","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:51.131364Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:f8855d5d3feba3b5356864139b54528f14f4af2dc1c386f62247c56fec3e6628","observation_id":"f2b1dbed-aa2f-49b8-b231-f64e3a40bb59","resolution":{"observed_at":"2026-08-06T17:28:56.879630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:56.679460Z","title":"libfuzzer – a library for coverage-guided fuzz testing,","venue":null,"work_id":"70a1c2bb-f0f2-40ed-985e-1b0dc61732d5","year":2018},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:51.208619Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:681fbc505e7dc2b48e58c93610b368ff0a66bc90ebec9ddb5a71e556610fa3b0","observation_id":"1edb009f-260c-4da6-bd56-6517e1ca281f","resolution":{"observed_at":"2026-08-06T17:28:56.728132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:56.563443Z","title":"Pastis: A collaborative approach to combine heterogeneous software testing techniques,","venue":null,"work_id":"f9ec9e8e-4ad1-4590-a0be-e5d1880c8ed0","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:51.287213Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:217c7b80ebeaebf46b4ad3ce2fdbfb22f20c20569ffe1d408f3c6bf29c57f018","observation_id":"0271b272-ae4d-4cd5-abdd-6bb0d0945132","resolution":{"observed_at":"2026-08-06T17:28:56.613530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:56.425978Z","title":"Slopt: Bandit optimization framework for mutation-based fuzzing,","venue":null,"work_id":"2765333d-fffa-4b6e-a869-d08e53385ee7","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:51.362623Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:8be484893a577db81e88bb068aba67245c14618726931ac9432e675c79b82450","observation_id":"54278483-9f15-460e-95bf-725d7600a672","resolution":{"observed_at":"2026-08-06T17:28:56.477045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:56.316998Z","title":"Gptfuzzer: Red teaming large language models with auto-generated jailbreak prompts,","venue":null,"work_id":"889a602c-9abb-44d6-98d5-6570757b1b11","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:51.433665Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:f1f8bc22ff8732b39fadf4669469abdef70c5934a9b4125236f2333b737673e9","observation_id":"d3451e22-526a-4dfb-84cb-7092a06756dc","resolution":{"observed_at":"2026-08-06T17:28:56.382079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:56.178773Z","title":"Large language models are zero-shot fuzzers: Fuzzing deep-learning libraries via large language models,","venue":null,"work_id":"e9fd5b2a-2720-40ba-9b9b-a0e7b71ac72b","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:51.523049Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:e14e7a4384267b62531ee631ddfccccf03131634e0de13a4b95dbc1e2ba360cd","observation_id":"d7fdfb73-fad9-4ed0-9e52-9ce1c640d68d","resolution":{"observed_at":"2026-08-06T17:28:56.236430Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:56.053987Z","title":"Fuzz4all: Universal fuzzing with large language models,","venue":null,"work_id":"c7c5cbc6-b03f-4c01-8a4f-46963c397ba4","year":2024},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:51.586098Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:9c3070e0f274634dfaaf9f4cee785b300e4f3e2eb2864531d6919d8dd00f342e","observation_id":"e3112e45-1103-4c67-81f8-90fafb6176cd","resolution":{"observed_at":"2026-08-06T17:28:56.119148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:55.915355Z","title":"Syzvegas: Beating kernel fuzzing odds with re- inforcement learning,","venue":null,"work_id":"28f267e4-02c2-4ccc-8e77-48f2db6c47fd","year":2021},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:51.674172Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:fb8ddd8c5c93ccfe668129955fb559152f39ad8140dc4abef5b68c31bbc890ae","observation_id":"a7acf850-c10c-4dd2-9945-79da08888756","resolution":{"observed_at":"2026-08-06T17:28:55.986034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:55.765951Z","title":"Fuzz- guard: Filtering out unreachable inputs in directed grey-box fuzzing through deep learning,","venue":null,"work_id":"aeb1111a-95f4-41ad-b859-3d8caf3ea353","year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:51.756138Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:b0e1c5d3a3354ee42270b29d7135eb2dc74077c38706f601b814a98a3303f716","observation_id":"fe9419e1-b97f-49f7-b04c-5eabe087db18","resolution":{"observed_at":"2026-08-06T17:28:55.832751Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:55.644163Z","title":"Compiler fuzzing through deep learning,","venue":null,"work_id":"be4f8058-f8fd-4fd9-a365-893ce75daf91","year":2018},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:51.861577Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:5c13af3bdd2732c8a37f35761d877b205905039a3b8e97bd7c84fdf28531f1ba","observation_id":"9244083b-f74c-4445-8cee-14288bf0060b","resolution":{"observed_at":"2026-08-06T17:28:55.687386Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:55.538320Z","title":"Evaluating and improving neural program- smoothing-based fuzzing,","venue":null,"work_id":"1bccff0e-6ad4-47e5-a350-1a7e03fdcdf6","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:51.981638Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:a73432f92bd392ff826c099b95d94042714bf64c6ee6f09dac82a44c92aa8402","observation_id":"6ad42443-6351-490e-94ed-d9fe6e53bb81","resolution":{"observed_at":"2026-08-06T17:28:55.571561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:55.410939Z","title":"Revisiting neural program smoothing for fuzzing,","venue":null,"work_id":"e5ba5eae-0319-4a3c-946e-673988bb3237","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:52.192593Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:c13b3159c6b62b2b1f0e4c5a0f59fe9dbf11953dbcd93b57dc34a6910efe0984","observation_id":"1589af73-e605-45d5-b046-0854c63a40da","resolution":{"observed_at":"2026-08-06T17:28:55.475695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:55.288138Z","title":"Deep reinforcement fuzzing,","venue":null,"work_id":"0d54b9c2-7f9a-409f-9aaf-dea86394563c","year":2018},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:52.339224Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:8f069d556acfe796b19095f30edc4e9ce5396f8f9e033fe5c9c22c7ad9ac4cef","observation_id":"c146a9c9-bb4b-4f90-82c9-85573e2edd36","resolution":{"observed_at":"2026-08-06T17:28:55.339463Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:55.151850Z","title":"Deepfuzz: Automatic generation of syntax valid c programs for fuzz testing,","venue":null,"work_id":"243a999b-9907-4dd5-8d9b-9c0f347e2d7c","year":2019},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:52.424322Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:50e0bb051794fbd3053adb882af298ecff0d526968bb707995c241115a3bd754","observation_id":"626171e2-feab-4ca0-973c-1526231598f5","resolution":{"observed_at":"2026-08-06T17:28:55.213105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:55.026918Z","title":"Rltrace: Synthesizing high- quality system call traces for os fuzz testing,","venue":null,"work_id":"e0647fe0-ec9d-44b0-bd08-2ecc8f8fedb0","year":2023},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:52.509138Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:09a0659c98650576b364e3826df13f81f472e602c9624a1c82bf192688a96e2c","observation_id":"049661c7-c9f3-4326-ae6c-baac25061d63","resolution":{"observed_at":"2026-08-06T17:28:55.098559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:54.920090Z","title":"Alphaprog: reinforcement generation of valid programs for compiler fuzzing,","venue":null,"work_id":"c8e5a849-b7cd-431f-9a1b-87481539a109","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:52.602796Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:255d6e1596b1c61e417075bf3e53d5fd8d9e9f13e6db5e2092a04ad6cea079fd","observation_id":"bc4a626f-b2bc-41a2-93cf-7c904de3eab1","resolution":{"observed_at":"2026-08-06T17:28:54.962438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:54.772121Z","title":"Evolutionary mutation-based fuzzing as monte carlo tree search,","venue":null,"work_id":"41ce2cb2-a72d-46a2-b17c-bba27f7bc5bd","year":2021},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:52.719239Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:7de116e0a55da7c00c838beb44fe2b162b527be65ff1800884cbe94d6d1c9491","observation_id":"e881517a-35cf-44a0-b075-9f9a2b56278c","resolution":{"observed_at":"2026-08-06T17:28:54.824515Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:54.655397Z","title":"One fuzzing strategy to rule them all,","venue":null,"work_id":"361e87d1-0f04-4174-b2bb-d8e26118ec2b","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:52.761942Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:d78995a03a1ad09a3da2e5d80a91f55322567f8de7861b70a9492f49fc1d6b96","observation_id":"9bfe31ef-0a95-4bb9-824d-68b70adcc1b6","resolution":{"observed_at":"2026-08-06T17:28:54.708239Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:54.531641Z","title":"Banditfuzz: fuzzing smt solvers with multi-agent reinforcement learning,","venue":null,"work_id":"5a2039a4-bdc3-4ce5-a035-397c09116a9b","year":2021},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:52.886679Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:1543fad02bbbb48fb0308b66ea04bee8878676460a9e463ad795b4bdbec3bf07","observation_id":"0c147982-0f36-4a70-8ac8-8b1634e9c4f7","resolution":{"observed_at":"2026-08-06T17:28:54.590945Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:54.420852Z","title":"Adaptive grey-box fuzz- testing with thompson sampling,","venue":null,"work_id":"be020a11-9fa3-473f-a127-f9397ee09d94","year":2018},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:52.992355Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:5fb9b6dfc0756cf407dc6e02947b071cf9121e06b48f17950d6b5796ee976999","observation_id":"bc0a597f-0cc2-4009-bc8e-29e97a5867b3","resolution":{"observed_at":"2026-08-06T17:28:54.472741Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:54.278719Z","title":"Effective seed scheduling for fuzzing with graph centrality analysis,","venue":null,"work_id":"ac21b012-0954-4549-be68-487967c1dac7","year":2022},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:53.048303Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:132cbd958da65087f715fcce126a11afccc3bb93cb50d74dcb39d71c7ed5044b","observation_id":"e907c69f-03c0-4cf1-8084-0765eccb424e","resolution":{"observed_at":"2026-08-06T17:28:54.347473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:54.160540Z","title":"The non- stochastic multiarmed bandit problem,","venue":null,"work_id":"9c43e9d9-3eb6-46da-b1aa-d4e786bd28ae","year":2002},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:53.082540Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:6a8a9b015e2a2565963ea33427357cf9e77664d9ca61aa57a6b576da45ac5e59","observation_id":"e05c16bb-5926-4e2e-ae9d-7a8050ba0941","resolution":{"observed_at":"2026-08-06T17:28:54.216827Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:54.044283Z","title":"syzkaller,","venue":null,"work_id":"55f6a2d0-c6b6-4a4c-bb49-46a89970e1c0","year":2016},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:53.147265Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:4e0ac525e210ea84218a861ac1bd27d2dea31614716fe9ebb71a6e7509d68545","observation_id":"72dab669-c6e2-483c-a38c-d7e19de9bbb1","resolution":{"observed_at":"2026-08-06T17:28:54.094721Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:53.924791Z","title":"A survey of compiler testing,","venue":null,"work_id":"ccbeabdb-26f1-441e-a78b-369601e4db78","year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:53.234972Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:9a9a44bf9d357b108117efa80e841fdf1f6045f1bc8b0dec2dbe6c45d0030207","observation_id":"5d254742-8bb6-4921-8ce3-018ac6843637","resolution":{"observed_at":"2026-08-06T17:28:53.977262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:53.804743Z","title":"Dsmith: Compiler fuzzing through generative deep learning model with attention,","venue":null,"work_id":"2dfc113c-365d-47ad-8b90-d7c742bbd5f2","year":2020},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:53.316360Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:2a126588a39bd5985e70d2193d4a408f622eafb3344eee9efe816e6d844cacf8","observation_id":"4ce9db8d-a2ff-4521-8178-31c0bc03dc9d","resolution":{"observed_at":"2026-08-06T17:28:53.858157Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:53.681508Z","title":"Let’s assume that we use the method in §3.1 to sched- ule three fuzzers throughout the fuzzing campaign: AFL, AFLFast and AFL++","venue":null,"work_id":"1996fb87-f9d3-4cd2-b57d-7737453ece13","year":null},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:53.394600Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:9156f2d811183845fd4cd885d6a29b666ef342297317f5649ab3263bdb6718d4","observation_id":"8c84105a-9040-415d-a332-5a748cdc39dd","resolution":{"observed_at":"2026-08-06T17:28:53.728338Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T17:28:53.577623Z","title":"Branch coverage","venue":null,"work_id":"cb45933e-8ac4-4756-a0e6-3586fe7bf6e5","year":1956},"citing_paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework","version":2},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-06T17:28:53.471180Z"},"links":{"citing_paper":"/paper/2507.10845"},"observation_digest":"sha256:45d1e4f76e82fa8e3dd0ed29b800c02cb7b92126693893299ad91330466d6a5f","observation_id":"256c77e7-369b-4d91-bc60-33c272929933","resolution":{"observed_at":"2026-08-06T17:28:53.619968Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.10845","last_updated":"2025-07-21T18:26:42Z","latest_version":2,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-06T17:21:37.835486Z","submitted_at":"2025-07-14T22:37:21Z","title":"BandFuzz: An ML-powered Collaborative Fuzzing Framework"},"reference_resolution":{"displayed":96,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":0,"verified_fuzzy":79},"total_outbound_references":96},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 96 of 96 outbound references and 2 inbound Pith citation observations for arXiv:2507.10845."}