{"as_of":"2026-08-23T01:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:722b226d57ac83e9310d054a2324d1ba9c15f346ea505423d25a5988c87a8549","coverage":[{"denominator":57,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":57,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T18:19:30.185207Z","state":"measured"},{"denominator":57,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":57,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.17353/citation-record","integrity":"/paper/2607.17353/integrity","json":"/paper/2607.17353/citation-record.json","paper":"/paper/2607.17353"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T18:19:24.289203Z","title":"Social-guard: Detecting scammers in online dating","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:24.289203Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:fbcad5d115e5890522a8431ccd2b7f55b9cfc2591e90bc8bd8e7d619f0521150","observation_id":"1846cb54-903c-413d-b8e0-f2afea358857","resolution":{"observed_at":"2026-08-01T18:19:24.289203Z","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":"2026-08-01T18:19:24.403572Z","title":"An automatic detection and analysis of the bitcoin generator scam","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:24.403572Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:35a29b60f017b7c7800141a389c5c06096606dbeffc66a4cb0fd7702c101f468","observation_id":"ae0580fa-4d59-4d53-bb70-f9fcbb4e0a01","resolution":{"observed_at":"2026-08-01T18:19:24.403572Z","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":"2026-08-01T18:19:24.502190Z","title":"game hack","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:24.502190Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:cd928109c43dcddc425f4c9e033c42bbebd1f868a1cd081fecce784026e85c6b","observation_id":"92495711-33e0-43a5-b208-5b9958f7608b","resolution":{"observed_at":"2026-08-01T18:19:24.502190Z","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":"2026-08-01T18:19:24.613832Z","title":"hello. this is the irs calling","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:24.613832Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:5bb1bd2e39357b6c4a7096e1c2adda0053c04e5f96c8b5caa2e595909762e5a3","observation_id":"64ccd8ef-1abb-4499-8013-7e8aacaaf189","resolution":{"observed_at":"2026-08-01T18:19:24.613832Z","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":"2026-08-01T18:19:24.783561Z","title":"Beyond phish: Toward detecting fraudulent e-commerce websites at scale","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:24.783561Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:a2df5d4eb3f3cdd827f29134fb14505d85cb86cc700f9c90b788362ba67c7df4","observation_id":"4b7393dc-bf34-459f-9412-272d4b75ccbf","resolution":{"observed_at":"2026-08-01T18:19:24.783561Z","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":"2026-08-01T18:19:24.909135Z","title":"Language models are few-shot learners","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:24.909135Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:03dc123e46891f19132e14120b5bcfc626c4e62af6b049ed8c5c0eb62e84ea98","observation_id":"bccb5b29-88c3-4a8a-9889-c784dc667e0d","resolution":{"observed_at":"2026-08-01T18:19:24.909135Z","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":"2026-08-01T18:19:25.019353Z","title":"Scam call detection using nlp and na¨ıve bayes classifier.INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:25.019353Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:7141b83fdac57e95a6db95759bfcc92461951b19813b1f69551b1394b311b771","observation_id":"2f645248-58a5-46f3-a2e4-1292d5672711","resolution":{"observed_at":"2026-08-01T18:19:25.019353Z","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":"2026-08-01T18:19:25.125319Z","title":"Learning to detect and mea- sure fake ecommerce websites in search-engine results","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:25.125319Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:a76e66c7adad65db84bcaf3526268e65c560840efa30250c759279512156701b","observation_id":"07ba0d1c-07af-4759-b61f-9b03a06a634b","resolution":{"observed_at":"2026-08-01T18:19:25.125319Z","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":"2026-08-01T18:19:25.244908Z","title":"Scam statistics, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:25.244908Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:0e53cad06276151b8e17b03b9ebf5d5e174cdce4b92d6bc5406232446a5eda34","observation_id":"9a090555-4152-465c-bf18-6e049253a496","resolution":{"observed_at":"2026-08-01T18:19:25.244908Z","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":"2026-08-01T18:19:25.333151Z","title":"Can ai keep you safe? a study of large language models for phishing detection","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:25.333151Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:afc3777ec1c3707145af3cf3414fa64f549f8c711a7779a2b0bbdcfd475d4d58","observation_id":"cc633081-62ea-49f8-b69d-8dcec0e25221","resolution":{"observed_at":"2026-08-01T18:19:25.333151Z","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":"2026-08-01T18:19:25.401510Z","title":"Scam detection in twitter","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:25.401510Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:ff597a5944e5c332c0dd73dc377f5f7c6f298c6d7cf483f51e5acbe696f25c05","observation_id":"78e0e611-5201-4b22-8a63-0ef1640dbc6d","resolution":{"observed_at":"2026-08-01T18:19:25.401510Z","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":"2026-08-01T18:19:25.484977Z","title":"New ftc data show a big jump in reported losses to fraud to $12.5 billion in 2024, 2025","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:25.484977Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:788eb2acdebe23207547d12994fa98672341f36db08d5b1e1bba7a50cc8d3258","observation_id":"9963eebd-93d4-421a-bcd5-6ee1b397ffc9","resolution":{"observed_at":"2026-08-01T18:19:25.484977Z","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":"2026-08-01T18:19:25.571114Z","title":"Understanding security issues in the nft ecosystem","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:25.571114Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:3fc6ab694bb61cea413f45124153051081f53e74f67fb1c911e6d1b35b92c08d","observation_id":"398bf4a2-88a3-4279-89c2-15dd9ad1c331","resolution":{"observed_at":"2026-08-01T18:19:25.571114Z","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":"2026-08-01T18:19:25.667382Z","title":"Hey chatgpt, is this message phishing? In2024 22nd Mediterranean Communication and Computer Networking Conference (MedComNet)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:25.667382Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:98eda744e71cf226ad5871f9f3669445f7d00c05242b8c64eb1bc3b887aa1a37","observation_id":"b8935ad8-3cb5-49b9-ab0b-903a8a14ae03","resolution":{"observed_at":"2026-08-01T18:19:25.667382Z","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":"2026-08-01T18:19:25.823573Z","title":"PentestGPT: Evaluating and harnessing large language models for automated penetration testing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:25.823573Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:5a71af7010255f2f6321f2c5eae3234d7739cfdc09f523d946f079116b110c70","observation_id":"58683d87-9e09-4237-8cca-c15daf5cfccd","resolution":{"observed_at":"2026-08-01T18:19:25.823573Z","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":"2026-08-01T18:19:25.985606Z","title":"PentestGPT: Evaluating and harnessing large language models for automated penetration testing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:25.985606Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:ef4aad748949b9e5d675124028b4724513e1cd95d8b6b66f22cbbcaa6862c7b8","observation_id":"edbd2b5a-08a1-4389-a002-6aa3aa76a176","resolution":{"observed_at":"2026-08-01T18:19:25.985606Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.04805","last_updated":"2019-05-24T20:37:26Z","snapshot_observed_at":"2026-08-14T18:16:28.847993Z","submitted_at":"2018-10-11T00:50:01Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.04805","snapshot_observed_at":"2026-08-01T18:19:26.050861Z","title":"Bert: Pre-training of deep bidirectional transformers for language un- derstanding.arXiv preprint arXiv:1810.04805, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:26.050861Z"},"links":{"cited_paper":"/paper/1810.04805","citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:f7ddf319aba98679c9827936ca05cad437e9c9091e3bc722b7a7bbdb9222d235","observation_id":"7338c67b-43ec-446f-96be-a694fb879357","resolution":{"observed_at":"2026-08-01T18:19:26.050861Z","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":"2026-08-01T18:19:26.159072Z","title":"Large language models for code analysis: Do LLMs really do their job? In33rd USENIX Security Symposium (USENIX Security ’24), pages 829–846, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:26.159072Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:ce4a6452c3c76cf8d758deaa3d4a98cf77d2a4bb75036a9857f9f31548ebd205","observation_id":"2e97b6a7-6a29-4e7e-b584-8d812afbe7a4","resolution":{"observed_at":"2026-08-01T18:19:26.159072Z","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":"2026-08-01T18:19:26.235893Z","title":"New study estimates as much as $75 billion in global victims’ losses to pig-butchering scam, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:26.235893Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:60107d12736b4edf1e1bdcea70d92551c4fdbfa304eedf1e82a9bf5350061894","observation_id":"937b69fc-9aac-4b8b-a6c1-8b26555678d2","resolution":{"observed_at":"2026-08-01T18:19:26.235893Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.16168","last_updated":"2022-10-28T14:43:13Z","snapshot_observed_at":"2026-08-16T16:20:19.174786Z","submitted_at":"2022-10-28T14:43:13Z","title":"Feature Engineering vs BERT on Twitter Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.16168","snapshot_observed_at":"2026-08-01T18:19:26.350797Z","title":"Feature engineering vs bert on twitter data.ArXiv, abs/2210.16168, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:26.350797Z"},"links":{"cited_paper":"/paper/2210.16168","citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:7bf45ff551c29849c7032251a9404f2f55f7c80bf6e12eb895ddaee205f9a2f9","observation_id":"0e1d3d16-e52e-4f85-a1f2-5e17e6564b91","resolution":{"observed_at":"2026-08-01T18:19:26.350797Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.13012","last_updated":"2021-01-12T15:48:52Z","snapshot_observed_at":"2026-08-18T19:09:21.659199Z","submitted_at":"2020-05-26T20:14:39Z","title":"Comparing BERT against traditional machine learning text classification","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.13012","snapshot_observed_at":"2026-08-01T18:19:26.407799Z","title":"Garrido-Merch ´an","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:26.407799Z"},"links":{"cited_paper":"/paper/2005.13012","citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:b84125960d19cac80671b37d9350e7a5ad40bd6b7d813fcbebe3a4a70fcecb07","observation_id":"bd2fc01a-bd2b-41db-b2ef-e940cc20bc15","resolution":{"observed_at":"2026-08-01T18:19:26.407799Z","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":"2026-08-01T18:19:26.477175Z","title":"How do crypto flows finance slavery? the economics of pig butchering.The Economics of Pig Butchering (February 29, 2024), 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:26.477175Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:a39877cfc1d1b5d4b97e93b4e2422c760c71207724734bd2f52035006ef9260e","observation_id":"aad6cdab-8f28-44e9-8fb0-9fd187e4cb91","resolution":{"observed_at":"2026-08-01T18:19:26.477175Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.06138","last_updated":"2020-10-13T03:25:15Z","snapshot_observed_at":"2026-08-16T19:13:57.919504Z","submitted_at":"2020-10-13T03:25:15Z","title":"Incorporating BERT into Parallel Sequence Decoding with Adapters","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.06138","snapshot_observed_at":"2026-08-01T18:19:26.562791Z","title":"Incorporating bert into parallel sequence decoding with adapters.ArXiv, abs/2010.06138, 2020","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:26.562791Z"},"links":{"cited_paper":"/paper/2010.06138","citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:1ba93a14218e2c456cb125e671dfa1eba95961352c3477797cc8e2f79322923e","observation_id":"7d2e3a68-d8a5-44f8-ab02-6428b378de60","resolution":{"observed_at":"2026-08-01T18:19:26.562791Z","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":"2026-08-01T18:19:26.634543Z","title":"Llm- tikg: Threat intelligence knowledge graph construction utilizing large language model.Computers & Security, 145:103999, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:26.634543Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:0cfd5b88d7aa5286f26181530188913d1cc7ad77ab27a094e3c800f96afe014f","observation_id":"4f3ed3dc-ab2f-4209-8df2-6bc0ce77790e","resolution":{"observed_at":"2026-08-01T18:19:26.634543Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10836","last_updated":"2023-09-19T15:14:42Z","snapshot_observed_at":"2026-08-16T14:59:24.386772Z","submitted_at":"2023-09-19T15:14:42Z","title":"CMRxRecon: An open cardiac MRI dataset for the competition of accelerated image reconstruction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.10836","snapshot_observed_at":"2026-08-01T18:19:26.716063Z","title":"Brown, Andrew Miller, Edward Chi, Anthony Michaud, Anselm Levskaya, Mostafa Dehghani, Michael Collins, and Lillian Lee","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:26.716063Z"},"links":{"cited_paper":"/paper/2309.10836","citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:607876469ee5dc361b3575cca64d45acfa09ea9497b93a8988a38ba3a4fdcb63","observation_id":"353a9197-f1d3-4b7d-9ac7-6c47f3196ef2","resolution":{"observed_at":"2026-08-01T18:19:26.716063Z","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":"2026-08-01T18:19:26.800123Z","title":"(security) assertions by large language models.IEEE Transactions on Information Forensics and Security, 19:4374–4389, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:26.800123Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:c37380400c3649ab56e0d5a71627c6e068c37fb3103d4714697ac6e68798868a","observation_id":"a4dbeca4-d9b5-4ce7-975c-d009f5c6c645","resolution":{"observed_at":"2026-08-01T18:19:26.800123Z","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":"2026-08-01T18:19:26.884241Z","title":"Surveylance: automatically detecting online survey scams","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:26.884241Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:41466cfef56a76a1699fcada8ee18007dce8d51e92a3d88d323e1997af6615e9","observation_id":"d413de2c-80c2-4a45-8169-0f4311c8c2aa","resolution":{"observed_at":"2026-08-01T18:19:26.884241Z","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":"2026-08-01T18:19:26.960680Z","title":"Chatphishdetector: Detecting phishing sites using large language models.IEEE Access, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:26.960680Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:d08c343c4a221bfc51021bed6f95a69a63939d526a19335109021f852880b3bc","observation_id":"827bc107-d174-4e8d-ad73-a31d3fcfa728","resolution":{"observed_at":"2026-08-01T18:19:26.960680Z","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":"2026-08-01T18:19:27.076260Z","title":"Scamdog millionaire: Detecting e-commerce scams in the wild","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:27.076260Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:72bf0ce934f63ef23836974f4b647c5910f65d94f0e48a4151d6b601ecf9a88d","observation_id":"27e85473-a24b-47d5-b3a4-7b0c85510721","resolution":{"observed_at":"2026-08-01T18:19:27.076260Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.20361","last_updated":"2025-05-24T06:22:42Z","snapshot_observed_at":"2026-08-17T09:16:12.379362Z","submitted_at":"2024-07-29T18:21:34Z","title":"From ML to LLM: Evaluating the Robustness of Phishing Webpage Detection Models against Adversarial Attacks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.20361","snapshot_observed_at":"2026-08-01T18:19:27.140519Z","title":"From ml to llm: Evaluating the robustness of phishing web- page detection models against adversarial attacks.arXiv preprint arXiv:2407.20361, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:27.140519Z"},"links":{"cited_paper":"/paper/2407.20361","citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:ac8feb049a79eafe35c09ba2a4e8586876b906ae5448759656a0ca3811f89bc9","observation_id":"13f183a9-67a9-49b3-b6a2-060a837c7c2f","resolution":{"observed_at":"2026-08-01T18:19:27.140519Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.01238","last_updated":"2023-05-07T10:57:51Z","snapshot_observed_at":"2026-08-17T16:47:59.863740Z","submitted_at":"2023-04-03T10:27:53Z","title":"Spam-T5: Benchmarking Large Language Models for Few-Shot Email Spam Detection","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.01238","snapshot_observed_at":"2026-08-01T18:19:27.178371Z","title":"Spam-t5: Benchmarking large language models for few-shot email spam detection.arXiv preprint arXiv:2304.01238, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:27.178371Z"},"links":{"cited_paper":"/paper/2304.01238","citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:f339b00b31521473a34c58cd96bb3d08c13eedc9c8796db39084ff905950e0a7","observation_id":"d5fe6cc1-250a-436c-a00e-cd75a61c0584","resolution":{"observed_at":"2026-08-01T18:19:27.178371Z","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":"2026-08-01T18:19:27.334657Z","title":"White, and Sujay Ku- mar Jauhar","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:27.334657Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:98112678f2a1f2245868ba6a6ea4edb1d9893bdf5cda68e425228d48c6b5f82d","observation_id":"8a80af38-4507-4561-88dd-2b1f338e2fe9","resolution":{"observed_at":"2026-08-01T18:19:27.334657Z","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":"2026-08-01T18:19:27.428315Z","title":"“hot” chatgpt: The promise of chatgpt in detecting and discriminating hateful, offensive, and toxic comments on social media.ACM Transactions on the Web, 18(2):1–36, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:27.428315Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:a7c0bac3f399395d7558cba2cca704a639f525ce79ba4868b49325791f06dc9f","observation_id":"3d5f4f24-6892-4393-a2a5-d387e829cbae","resolution":{"observed_at":"2026-08-01T18:19:27.428315Z","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":"2026-08-01T18:19:27.482425Z","title":"KnowPhish: Large language mod- els meet multimodal knowledge graphs for enhancing Reference-Based phishing detection","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:27.482425Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:e28241254b606e7473393d364bccdae75082378cc27c9261557ea36fcb10c6fa","observation_id":"2bc23581-43c6-4aaf-ac47-1f512ee42055","resolution":{"observed_at":"2026-08-01T18:19:27.482425Z","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":"2026-08-01T18:19:27.564783Z","title":"Exploring ChatGPT’s capabilities on vulnerability management","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:27.564783Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:3b05cac632cb9842e6a7156f702fc667b110e9d291c743e516eccb1b23774837","observation_id":"0f9371ef-59f3-4b51-b1f7-16062666376d","resolution":{"observed_at":"2026-08-01T18:19:27.564783Z","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":"2026-08-01T18:19:27.654539Z","title":"Exploring ChatGPT’s capabilities on vulnerability management","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:27.654539Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:2fd293dc252bb5841767d4dc0ae44b93d0167e067e0fb6fe126c824b4864e467","observation_id":"a3c33113-b0e9-4caf-acb0-dc1be28c22b8","resolution":{"observed_at":"2026-08-01T18:19:27.654539Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08786","last_updated":"2022-03-03T12:10:58Z","snapshot_observed_at":"2026-08-18T15:42:46.886862Z","submitted_at":"2021-04-18T09:29:16Z","title":"Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08786","snapshot_observed_at":"2026-08-01T18:19:27.751672Z","title":"Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity.arXiv preprint arXiv:2104.08786, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:27.751672Z"},"links":{"cited_paper":"/paper/2104.08786","citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:2c5614457fee164e4300b39ca710438514febdc5230538b1b0d883022d3786db","observation_id":"92e0e376-9fa1-41cc-b61d-317097a6fd04","resolution":{"observed_at":"2026-08-01T18:19:27.751672Z","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":"2026-08-01T18:19:27.835680Z","title":"Large language model guided protocol fuzzing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:27.835680Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:1fa8c7babf8f744eb11c2ca70fd420570b5277f05394d90b9259c1b78cc79164","observation_id":"8e52572e-951c-456c-9c1d-927d7e97d789","resolution":{"observed_at":"2026-08-01T18:19:27.835680Z","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":"2026-08-01T18:19:27.914515Z","title":"Dial one for scam: Analyzing and detecting technical support scams","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:27.914515Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:bd552ee5fab7da4da0f4af8719571fd9701be60d9b3bf3996e8a6d75dfc2af4c","observation_id":"9b92e6c4-8b8e-43f3-9f0f-c91e4b4e9ba4","resolution":{"observed_at":"2026-08-01T18:19:27.914515Z","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":"2026-08-01T18:19:27.985177Z","title":"On sms phishing tactics and infrastructure","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:27.985177Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:fbf66bc97ef0f89e3f575392544ef5d3540cad35f452e91e335e1408c3e153c8","observation_id":"5ebd56e7-586a-4ba5-a835-2d84ec254b7e","resolution":{"observed_at":"2026-08-01T18:19:27.985177Z","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":"2026-08-01T18:19:28.060083Z","title":"Norton genie your free ai-powered scam detector, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:28.060083Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:c02c5ec74b0f55fdb0d9e37b6aa486c4a25473a10f2d83e3fae758a1277f89c9","observation_id":"6acfb462-dc04-4d72-b63d-952259179531","resolution":{"observed_at":"2026-08-01T18:19:28.060083Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1806.01156","last_updated":"2018-12-17T14:35:30Z","snapshot_observed_at":"2026-08-21T07:02:16.921313Z","submitted_at":"2018-06-04T15:10:27Z","title":"Tranco: A Research-Oriented Top Sites Ranking Hardened Against Manipulation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.01156","snapshot_observed_at":"2026-08-01T18:19:28.147212Z","title":"Tranco: A research-oriented top sites ranking hardened against manipulation.arXiv preprint arXiv:1806.01156, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:28.147212Z"},"links":{"cited_paper":"/paper/1806.01156","citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:5b433180e1b997b2273968935ac6dcd25d0252cd3c97b386ff400b3e1df5e6ec","observation_id":"d8eb09a4-b8c5-42fe-bee3-aa06dbe703f8","resolution":{"observed_at":"2026-08-01T18:19:28.147212Z","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":"2026-08-01T18:19:28.212795Z","title":"Resource networks of pet scam websites","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:28.212795Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:414e958c1bc5005d66ff142be93ed5614e763a10c194ccb03afbc7221b01450e","observation_id":"d2b95e4c-8c49-4feb-b5d8-8b6eb2202774","resolution":{"observed_at":"2026-08-01T18:19:28.212795Z","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":"2026-08-01T18:19:28.289287Z","title":"Reddit r/scams, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:28.289287Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:de65d27330523c1042c563dc6da3f9cb0c0319212ea356b56a402ad0c712c915","observation_id":"e63bf6bd-3659-4240-859b-14d62f919059","resolution":{"observed_at":"2026-08-01T18:19:28.289287Z","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":"2026-08-01T18:19:28.369285Z","title":"From chatbots to phishbots?: Phishing scam generation in commercial large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:28.369285Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:10bf1140319b15e46625f5135a54b7bfcbd6175748d586c2eb4adbefc4514112","observation_id":"d20d6ef9-218a-4569-b362-da6785e39b44","resolution":{"observed_at":"2026-08-01T18:19:28.369285Z","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":"2026-08-01T18:19:28.563835Z","title":"Investigating evasive techniques in sms spam filtering: A comparative analysis of machine learning models.IEEE Access, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:28.563835Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:6b237973a6223c1f80ff109bb31ea71784a9108ab41446fe1e475ec5cec2c4b8","observation_id":"c77014d4-3797-47ee-b1fa-ff8836c8821b","resolution":{"observed_at":"2026-08-01T18:19:28.563835Z","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":"2026-08-01T18:19:28.742151Z","title":"Your anti-scam partner, keeping you safe!, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:28.742151Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:a077f632dd1c1319eade5131a084fab9adaaded78451ba6f5d866e317acddc5d","observation_id":"1e764ce7-ad6c-46fa-9732-9040597edff0","resolution":{"observed_at":"2026-08-01T18:19:28.742151Z","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":"2026-08-01T18:19:28.917086Z","title":"Detection of internet scam using logistic regression","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:28.917086Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:56381c12ab268e5bea2f78e6ef0ce2612a35cffe49ed0ba2d6891393bf53f63f","observation_id":"5adbea73-4397-4832-8d7a-56b348592f8b","resolution":{"observed_at":"2026-08-01T18:19:28.917086Z","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":"2026-08-01T18:19:29.032046Z","title":"Outside the closed world: On using machine learning for network intrusion detection","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:29.032046Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:a8480fed45aafa5a1a4fe388f00faf4e61d9bee0d40698333ead37e064f72867","observation_id":"601baea8-3eb8-4ad8-b129-fd9f9e52cda4","resolution":{"observed_at":"2026-08-01T18:19:29.032046Z","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":"2026-08-01T18:19:29.175261Z","title":"Exposing search and advertisement abuse tactics and infras- tructure of technical support scammers","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:29.175261Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:ae04f627709461aa50faa5cfe2cc26b22a1a84afa2b5f01bfb21fe4271d21d29","observation_id":"42d0c5f2-c1db-464c-bd18-638b48481f9e","resolution":{"observed_at":"2026-08-01T18:19:29.175261Z","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":"2026-08-01T18:19:29.294861Z","title":"Automatically dismantling online dating fraud.IEEE Transactions on Information Forensics and Security, 15:1128–1137, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:29.294861Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:d01fd0df8ff2e09d85636f5fd74f60aff36fa56771df59c9c6099602e6a9a186","observation_id":"20bffe97-5faa-4c99-b058-a8730a7a48f8","resolution":{"observed_at":"2026-08-01T18:19:29.294861Z","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":"2026-08-01T18:19:29.431803Z","title":"An innovative GPT-based open-source intelligence using historical cyber incident reports.Natural Language Processing (NLP) Journal, page 100074, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:29.431803Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:1b3caf838922de316e261f8fe3ca6fe4de11944592f1e509b3f359b9b342e346","observation_id":"1c77481a-06e7-4ff7-9055-cff2d1be41f8","resolution":{"observed_at":"2026-08-01T18:19:29.431803Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-01T18:19:29.560634Z","title":"Llama: Open and efficient foundation language models.arXiv preprint arXiv:2302.13971, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:29.560634Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:4a87d5b5885cdec5fbc574611e36eb9b44d3431aeeb7c2b5c126e3acf3b48ba2","observation_id":"b55046f4-9c68-418c-a70e-c238405003ea","resolution":{"observed_at":"2026-08-01T18:19:29.560634Z","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":"2026-08-01T18:19:29.711314Z","title":"Attention is all you need.Advances in neural information processing systems, 30, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:29.711314Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:3fb62ec0e4e557319b68ac1febdc3df2531c5edcfd6c0ed1d9cabc62a7f63641","observation_id":"66db601a-d931-4376-aa46-10384bbad4a4","resolution":{"observed_at":"2026-08-01T18:19:29.711314Z","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":"2026-08-01T18:19:29.850990Z","title":"Counterfighting counterfeit: detecting and taking down fraudulent webshops at a cctld","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:29.850990Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:1d2232bc4a04473b3ea498f5b82b69980254967c87d6f86bd139c444ebb6b5c9","observation_id":"c5add03d-2cc3-4f00-aadc-6832d2d94d86","resolution":{"observed_at":"2026-08-01T18:19:29.850990Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.11903","last_updated":"2023-01-10T23:07:57Z","snapshot_observed_at":"2026-08-13T07:04:41.220509Z","submitted_at":"2022-01-28T02:33:07Z","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.11903","snapshot_observed_at":"2026-08-01T18:19:30.015675Z","title":"Chain of thought prompting elicits reasoning in large language models.arXiv preprint arXiv:2201.11903, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:30.015675Z"},"links":{"cited_paper":"/paper/2201.11903","citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:e8ca9fa22c0e0c87fad82ed84483ea6e88c4dcd504caa49e877b028922b9fc0c","observation_id":"a06d1c53-c968-4e6b-a39a-342c498d8a2b","resolution":{"observed_at":"2026-08-01T18:19:30.015675Z","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":"2026-08-01T18:19:30.185207Z","title":"Who are the phishers? phishing scam detection on ethereum via network embedding.IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52:1156–1166, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-01T18:19:30.185207Z"},"links":{"citing_paper":"/paper/2607.17353"},"observation_digest":"sha256:1baebe1a95e07b66593e4ad871743f0311b1d745e3f01dab5a1b623dd510dc7a","observation_id":"3c4b86f4-327c-4307-a4a0-1fe8ab7a898e","resolution":{"observed_at":"2026-08-01T18:19:30.185207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.17353","last_updated":"2026-07-19T17:28:36Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-21T04:28:56.979052Z","submitted_at":"2026-07-19T17:28:36Z","title":"Measuring and Evaluating the Performance of Generative AI Models for Scam Detection"},"reference_resolution":{"displayed":57,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":57,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":57},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2607.17353."}