{"as_of":"2026-08-22T21:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:012c906e26f50b21279f9d5121266367728debe528450230b48b6fa0cea0dc31","coverage":[{"denominator":35,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":35,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:57:32.727530Z","state":"measured"},{"denominator":36,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":36,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:57:32.727530Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-14T12:57:32.773368Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"cited_work":{"arxiv_id":"1908.06148","doi":null,"metadata_source":"pith","pith_arxiv_id":"1908.06148","snapshot_observed_at":"2026-08-14T12:57:32.773368Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","venue":"cs.CR","work_id":"75460064-86a5-4007-8735-cbf8c074ad92","year":2019},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.727530Z"},"links":{"cited_paper":"/paper/1908.06148","citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:76015875d6b26f4fd58639e6f7222f107bc056af91b8beaffcea224c43064a73","observation_id":"e449df3e-10a0-453c-af53-8ddfdfc522a8","resolution":{"observed_at":"2026-08-14T12:57:32.777483Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1908.06148/citation-record","integrity":"/paper/1908.06148/integrity","json":"/paper/1908.06148/citation-record.json","paper":"/paper/1908.06148"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:33.145074Z","title":"Sceadan: Using Concate- nated N-Gram Vectors for Improved File and Data Type Classiﬁcation,","venue":null,"work_id":"db9bc930-30d3-4873-b7db-e8dffd64638a","year":2013},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.603198Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:82aa9f92859eb883f75d0b0ccaa51d753a1475fd6f5a6fc00242043bd9c2804c","observation_id":"8aa9d36b-ff0d-4d9d-af27-e592ca8369d0","resolution":{"observed_at":"2026-08-14T12:57:33.149226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:33.134554Z","title":"Using NLP techniques for ﬁle fragment classiﬁcation,","venue":null,"work_id":"7bf6bbe5-85c3-4a8e-b4a5-5d22e88e5c99","year":2012},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.608423Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:43a31fbd3724bcac57e320b2c7457080ff33f4dfdcefc9792d295fc986bde525","observation_id":"d3dfc217-e2e5-4cfc-824f-c76b70fe1043","resolution":{"observed_at":"2026-08-14T12:57:33.138353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:33.123448Z","title":"Statistical Disk Cluster Classiﬁcation for File Carving,","venue":null,"work_id":"a7bdd021-04f2-41c3-be15-424092daeaed","year":2007},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.612105Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:0e53d48b52a619c151aeac3f6b61d4f37ee79c6077839b8314cd840883b17e3e","observation_id":"f429199f-72ea-4475-a669-c7badfde6bd7","resolution":{"observed_at":"2026-08-14T12:57:33.127375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:33.112168Z","title":"Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classiﬁcation,","venue":null,"work_id":"4bc09f01-04bc-40c2-b71a-8cb449bd7336","year":2018},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.616211Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:a9f1bf8e1f194cc46ece24a9a02e994d090b556ee53255fecd66e4d40728a6c6","observation_id":"3de70928-baf2-44bc-b471-7c7ea327557a","resolution":{"observed_at":"2026-08-14T12:57:33.116522Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:33.101825Z","title":"Cocost: a computational cost efﬁcient classiﬁer,","venue":null,"work_id":"db8e1c4b-4bcd-4610-8331-d6821532fefc","year":2009},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.620332Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:b2e90ae0f4564ac4c910e7b2ff1d6bd2c9973e4a8bc0c7e520d5fe434c8ad78d","observation_id":"2693ed06-2e72-4c91-9e7d-e1a7da3a9089","resolution":{"observed_at":"2026-08-14T12:57:33.105446Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:33.090845Z","title":"Jpgcarve: An advanced tool for automated recovery of fragmented jpeg ﬁles,","venue":null,"work_id":"7417fbc1-89e4-4516-abad-f3c790da1422","year":2016},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.624199Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:df1b4dc23028d182a559d6ccd3427c45758e5b78c98f86d972106d1c4238b7a3","observation_id":"5a4991a6-30a8-4871-865e-bfa8e066763a","resolution":{"observed_at":"2026-08-14T12:57:33.094568Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:33.079698Z","title":"File Type Identiﬁcation of Data Fragments by Their Binary Structure,","venue":null,"work_id":"1096866a-b943-4513-a23a-76a61a9b07f5","year":2006},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.628114Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:7bc36fc5bf0c61d50deaae74ce5a0ca0b1f40bca3077e6c63a660165707b3899","observation_id":"cc3c65c4-0bca-4d21-ad1f-e578711c20fd","resolution":{"observed_at":"2026-08-14T12:57:33.083738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:33.068709Z","title":"Predicting the types of ﬁle fragments,","venue":null,"work_id":"35f42aad-9a75-476f-9ea3-fb69840482a8","year":2008},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.631664Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:8d0aa3cc171c5cfd78cc5cd5643ade2bfd70d0f93781e54ae5d2fc8c36344bd1","observation_id":"f973cfda-37ad-4479-b1de-67263347d001","resolution":{"observed_at":"2026-08-14T12:57:33.072335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:33.057323Z","title":"A File Fragment Classiﬁcation Method Based on Grayscale Image,","venue":null,"work_id":"bbf03e7a-8cc5-47f9-b72d-4dc0fc375715","year":2014},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.635666Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:32a7cf64aabbafa06e643195927e04e5e101b5961feb1aa342c89d056487c71a","observation_id":"9bc30b3d-4e97-4a37-b3f3-ebfa498be957","resolution":{"observed_at":"2026-08-14T12:57:33.061479Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:33.046097Z","title":"JPEG Recovery Lab,","venue":null,"work_id":"02c26b5a-de20-4274-9b26-8d3fe76a749a","year":2019},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.639103Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:66c3eda08bb93fa5a97268ace2a0c8591e645cea1d2947289f8b7b485faccef7","observation_id":"dc8c8d3d-9d44-47b1-97c8-4ffd75823d05","resolution":{"observed_at":"2026-08-14T12:57:33.049865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:33.033438Z","title":"Carving orphaned jpeg ﬁle fragments,","venue":null,"work_id":"e448d008-c65f-425f-a1fd-b2da6934895d","year":2015},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.642596Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:7853b59d26f4113a09fae3169ec01f620982eaaebd82bf78f9bd5ce0249db7d6","observation_id":"64c54d23-a642-4d56-bc09-1647d72cc9bd","resolution":{"observed_at":"2026-08-14T12:57:33.037203Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:33.021838Z","title":"Every shred helps: Assembling evidence from orphaned jpeg fragments,","venue":null,"work_id":"0b34352d-8680-4e65-b626-fb82bbbe718d","year":2019},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.646230Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:a638cc994b845a12f87929336aa394f913740ddae4edec127f78277d85309cd9","observation_id":"722981b2-cffa-4129-8758-e9a51cadddf5","resolution":{"observed_at":"2026-08-14T12:57:33.026187Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1301.3781","last_updated":"2013-09-07T00:30:40Z","snapshot_observed_at":"2026-07-06T03:04:11.148340Z","submitted_at":"2013-01-16T18:24:43Z","title":"Efficient Estimation of Word Representations in Vector Space","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1301.3781","snapshot_observed_at":"2026-08-14T12:57:32.649843Z","title":"Efﬁcient estimation of word representations in vector space,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.649843Z"},"links":{"cited_paper":"/paper/1301.3781","citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:c8b87bf602d1c54246a2333c8b703710057b295c956af4b9d9b8b7ab6cc76291","observation_id":"424ee352-0a80-4129-be38-dca7af94ec79","resolution":{"observed_at":"2026-08-14T12:57:32.649843Z","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":"2026-08-14T12:57:33.010470Z","title":"File fragment classiﬁcation using neural networks with lossless representations,","venue":null,"work_id":"3c3b855b-32be-4f00-bd2b-def4a53c5d4f","year":2018},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.653835Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:a6862c32641b6b26b9f895224da31dea3531bd1b4de487cd51ed65f9c70218d7","observation_id":"fb4f9220-d3c8-4fd3-9816-d744d9aa7112","resolution":{"observed_at":"2026-08-14T12:57:33.014695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.998903Z","title":"File Fragment Classiﬁcation Using Grayscale Image Conversion and Deep Learning in Digital Forensics,","venue":null,"work_id":"e366311d-bf5c-4379-ad3f-db4bf02abe3e","year":2018},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.657355Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:70503de3bbf6766358d05a7eded718710c0e3c2620670041438dfe7cc8effe61","observation_id":"94a15af6-5e7d-477a-a88a-f2cae90364d9","resolution":{"observed_at":"2026-08-14T12:57:33.002845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.988512Z","title":"Overview of the high efﬁciency image ﬁle format,","venue":null,"work_id":"b59d90bb-0436-4b47-b1b9-71102945a5b2","year":2015},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.660596Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:457b33c0f55145bab9516a3ad298811d3e6b804f35398828d793f510005ab4c9","observation_id":"f7a406bd-fc1c-4502-b2af-fd1b15a69d50","resolution":{"observed_at":"2026-08-14T12:57:32.992176Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.977582Z","title":"Algorithms for hyper- parameter optimization,","venue":null,"work_id":"b35911f3-b242-4708-b79a-de0ab46ad7e2","year":2011},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.664247Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:97de5847e23790e405c16fc8795ddaf9a20adb323100ae8b6a121148a1f0a7a1","observation_id":"2fa0c4b6-df81-497c-97d3-4ec9e9ab1572","resolution":{"observed_at":"2026-08-14T12:57:32.981566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.966729Z","title":"The jpeg still picture compression standard,","venue":null,"work_id":"ffc9c20b-706a-41ec-a37c-ddb027013cfc","year":1992},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.667629Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:bb7a94d2ff8ffec0eb16dec4ff623a2ecfe55e2c8336d25844be656ed3fd8363","observation_id":"d032e132-207d-4dae-904c-e8de5c8f519a","resolution":{"observed_at":"2026-08-14T12:57:32.970937Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.955524Z","title":"A Fragment Classiﬁcation Method Depending on Data Type,","venue":null,"work_id":"ac175e5b-12bc-446b-bdda-c04e464f38f0","year":2015},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.671088Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:ba7963f7e7ca9f22ff2f7cfda1b023738a4645a2879f7b15dadf8dd25d09fa0b","observation_id":"307d0d39-989a-4798-a847-14e1dacaf655","resolution":{"observed_at":"2026-08-14T12:57:32.959808Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.944406Z","title":"Data Type Classiﬁcation: Hierarchical Class-to-Type Modeling,","venue":null,"work_id":"cc48094a-9cdf-4013-baf2-a8c469fb9f77","year":2016},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.674546Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:ee4a60dcc2cf0d87c6d9d3cbdf31803252efb640ff54fdd921233dbe2f26d1fe","observation_id":"7232e8c0-7e0c-4e63-a387-0a78020a2f4d","resolution":{"observed_at":"2026-08-14T12:57:32.948491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.21227/kfxw-8084","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.756065Z","title":"File fragment type (fft) - 75 dataset,","venue":null,"work_id":"b0eadaf6-9c6c-4943-8455-376d555b16e5","year":2019},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.678357Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:571328a4db84d49b781767e653b5afad6f192b58c5d06a837495d3abfd74eb31","observation_id":"5fdc1b4e-bfdc-4c63-af0b-5056f782a088","resolution":{"observed_at":"2026-08-14T12:57:32.762362Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.931836Z","title":"GovDocs Dataset,","venue":null,"work_id":"32f144b1-47de-4fe3-97ca-636f52857544","year":2019},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.681973Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:5a9acee0f9f36429384da056273d6fab85557c5e1b51db7a65d661bbdbbe6ae1","observation_id":"425a18ac-1b95-4d18-8447-39af5b1b3c8b","resolution":{"observed_at":"2026-08-14T12:57:32.936687Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.919659Z","title":"Intel Movidius Myriad X VPU,","venue":null,"work_id":"34bc7049-a068-410b-b741-471d88b016a4","year":2019},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.685388Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:07bc53ab6b961ee5b7a1d8e82df7399d8d890c106584291648fb95e69a55c666","observation_id":"846dfd10-b138-49d7-940a-3ea569f242bf","resolution":{"observed_at":"2026-08-14T12:57:32.923584Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.907521Z","title":null,"venue":null,"work_id":"cd3c2304-fa99-46cd-abab-b99c55a5874d","year":2015},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.688625Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:ee42e74b8361e6dfe34f3b5125e3edc0b68ce43d19a42f59eb65bb50d5b19e43","observation_id":"7bf0b3e1-97b0-47b6-b174-25819e97456e","resolution":{"observed_at":"2026-08-14T12:57:32.911275Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.895569Z","title":"Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures,","venue":null,"work_id":"b7f29fad-1da1-4134-8d7b-6670e37641e0","year":2013},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.692091Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:9611d7cca771be99a79dddb8bd815c1228987aa60f4f9dd0e32010e3a092132f","observation_id":"dc281df4-37d9-4387-9e2b-25af2931cc63","resolution":{"observed_at":"2026-08-14T12:57:32.899433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.884170Z","title":"Sequential model-based optimization for general algorithm conﬁguration,","venue":null,"work_id":"99237677-f96c-4791-8917-421b612f03dd","year":2011},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.695728Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:95b03ccfbca1e16e81b3dcc11e574f0158ffcee4bba04d9f2378a87f7e557752","observation_id":"b29d3711-5b2f-494a-b640-1b7bf8b1c012","resolution":{"observed_at":"2026-08-14T12:57:32.888220Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.873418Z","title":"Bz2 package,","venue":null,"work_id":"46def16f-1fbe-4f06-bd80-e78f38d32153","year":2019},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.699145Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:1a457d7e6a29973c5b55a42bddd871b19ebdfdbb0bf5fb42c7360b12d00cbf7a","observation_id":"934ece72-920e-450f-82d5-aa749985d87f","resolution":{"observed_at":"2026-08-14T12:57:32.877414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.860835Z","title":"Zlib package,","venue":null,"work_id":"1dda807d-ddf4-427a-978c-e2794a65d265","year":2019},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.702379Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:f81fe3db61d22148dc02acd035b1d3d3b19b13bfc387ae90d95d82ed589157d6","observation_id":"28b5691a-cb1f-42d4-8c34-e4ff81fb0047","resolution":{"observed_at":"2026-08-14T12:57:32.866018Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.848707Z","title":"Sceadan - open source implementation,","venue":null,"work_id":"9a1775fb-26c9-4579-82e8-99a330c4e10d","year":null},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.706079Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:932bf4eb1970d70e258d889b141bc5c9201a50af27a9878686a23d257d5c305e","observation_id":"70253f94-15bc-480b-84e2-7cce253d13ae","resolution":{"observed_at":"2026-08-14T12:57:32.853081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.837210Z","title":"Everything you need to know about the JPEG-killing HEIF for- mat Apple is adopting,","venue":null,"work_id":"f708f7a3-97ca-4fd3-a615-32d8c8e887d9","year":2019},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.709669Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:9eaaa8cba1ce9eb6da2580eb456812324d0a34ea9555358bad712b2bc2901244","observation_id":"c8672810-7c50-4913-b5d1-96cd3947be27","resolution":{"observed_at":"2026-08-14T12:57:32.841454Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.826624Z","title":"Overview of the high efﬁciency video coding (hevc) standard,","venue":null,"work_id":"ba208a44-c42e-4af6-a5dd-46bbd2c53663","year":2012},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.712966Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:ac37ba5171f71a9da43286010f2267d615b5459c57879833a96af6e560fc57b3","observation_id":"825c6b4b-dc50-4128-a225-080019a1281f","resolution":{"observed_at":"2026-08-14T12:57:32.830292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:57:32.816110Z","title":"Progressive neural architecture search,","venue":null,"work_id":"b73cc92f-1ee7-464a-83ba-feee8fe3f887","year":2018},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.716639Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:27bb79f546d8204391b245aded650c9f30205e553582dc1b1c9d830642b6964a","observation_id":"6dc9810c-e201-40df-9615-075e410a87b8","resolution":{"observed_at":"2026-08-14T12:57:32.819832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.01569","last_updated":"2019-04-08T17:50:26Z","snapshot_observed_at":"2026-08-19T09:11:01.923741Z","submitted_at":"2019-04-02T17:57:16Z","title":"Exploring Randomly Wired Neural Networks for Image Recognition","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.01569","snapshot_observed_at":"2026-08-14T12:57:32.720143Z","title":"Exploring randomly wired neural networks for image recognition,","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.720143Z"},"links":{"cited_paper":"/paper/1904.01569","citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:733a37ffc8f942b066173426b2ae21848a921e03bfd9c45c634e98b3c19c788e","observation_id":"a83d120a-c6e8-40e7-a72e-eeadc53d64ee","resolution":{"observed_at":"2026-08-14T12:57:32.720143Z","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":"2026-08-14T12:57:32.805043Z","title":"Benchmarking state-of-the-art deep learning software tools,","venue":null,"work_id":"8c1c45df-f706-4cfc-95b6-d82397223db4","year":2016},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.724055Z"},"links":{"citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:ce9bb47b201bb20d4866320905b5183a5e65261948b5e0286b623780be80f1e9","observation_id":"4cb124ca-2da1-44cc-a3dc-37890fe26e15","resolution":{"observed_at":"2026-08-14T12:57:32.809292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"cited_work":{"arxiv_id":"1908.06148","doi":null,"metadata_source":"pith","pith_arxiv_id":"1908.06148","snapshot_observed_at":"2026-08-14T12:57:32.773368Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","venue":"cs.CR","work_id":"75460064-86a5-4007-8735-cbf8c074ad92","year":2019},"citing_paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T12:57:32.727530Z"},"links":{"cited_paper":"/paper/1908.06148","citing_paper":"/paper/1908.06148"},"observation_digest":"sha256:76015875d6b26f4fd58639e6f7222f107bc056af91b8beaffcea224c43064a73","observation_id":"e449df3e-10a0-453c-af53-8ddfdfc522a8","resolution":{"observed_at":"2026-08-14T12:57:32.777483Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.06148","last_updated":"2020-06-07T05:13:26Z","latest_version":2,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-14T12:52:12.170104Z","submitted_at":"2019-08-16T19:53:46Z","title":"FiFTy: Large-scale File Fragment Type Identification using Neural Networks"},"reference_resolution":{"displayed":35,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":3,"verified_exact":1,"verified_fuzzy":30},"total_outbound_references":35},"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 22 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:1908.06148."}