{"as_of":"2026-08-13T05:33:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:17d4e46db96272161206534caec60eab638f9fb2d0e17877ccad437618bb2051","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T11:59:22.870551Z","state":"measured"},{"denominator":47,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":47,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2411.17621/citation-record","integrity":"/paper/2411.17621/integrity","json":"/paper/2411.17621/citation-record.json","paper":"/paper/2411.17621"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:23.965058Z","title":null,"venue":null,"work_id":"d9657a66-5ad4-43e9-ab70-49ddbd282f5d","year":2021},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.727092Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:c654bf1f10faac10ac69f1040274bc438090805358ccfe9c2bb3291af08e62c8","observation_id":"2343db7e-178a-4a47-8bb2-a7e9d32587fa","resolution":{"observed_at":"2026-08-12T11:59:23.968268Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.948356Z","title":"Buffer overflow vulnerabilities and attacks explained,","venue":null,"work_id":"85383192-d294-48a6-877c-5c6cb3953ae8","year":null},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.734263Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:dda6182bebed4ec1613a1d063b110bbe31f80337e711ad741758f9ae17686e44","observation_id":"f19cd2b1-6dd7-448e-b5f2-75b96fc0b567","resolution":{"observed_at":"2026-08-12T11:59:23.951572Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.939594Z","title":"Internet Crime Report,","venue":null,"work_id":"e1aac974-7b8c-4350-b4a1-c0000e95daa9","year":2019},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.737460Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:05f49cebb7b5f8d212206932bfaee2e503530820c11bbb22ad047edca5c2bba1","observation_id":"071d62fa-2435-4bf7-ad85-abaa2bc1bceb","resolution":{"observed_at":"2026-08-12T11:59:23.942711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.930926Z","title":"533 million Facebook users’ phone numbers and personal data have been leaked online,","venue":null,"work_id":"9b9990b0-537e-4650-b736-3e8aeb46ee3d","year":2021},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.740875Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:2edc5914550da92263067f2dca1b1922c78f58d36beaab60130165098a2e13b4","observation_id":"a5ff1989-0363-4ea5-a70b-40f4626dc5fb","resolution":{"observed_at":"2026-08-12T11:59:23.934373Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"7716.35877","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:23.731482Z","title":"Multiclass Classification of Software Vulnerabilities with Deep Learning,","venue":null,"work_id":"ca0583ca-7014-41d6-ac0b-3d9c7fb0db57","year":2023},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.744085Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:fe94f29f805644fb546781115af20de752373772aec5a57687eb21ab1a2618f1","observation_id":"e1e18fe2-2fc9-4aa4-827d-649bfb603718","resolution":{"observed_at":"2026-08-12T11:59:23.738088Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.921253Z","title":"VMware Flaw a Vector in SolarWinds Breach?,","venue":null,"work_id":"7f627a3a-acd2-40ba-98bc-3d525a748b2b","year":2020},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.747325Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:40deb7641bc783fd5c09b2fd0c59a7f756b27996f7d6c48deec627d84163b3f0","observation_id":"5141802c-d3cc-497c-8c0f-6b1102d14341","resolution":{"observed_at":"2026-08-12T11:59:23.924755Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.911348Z","title":"Predicting malware attributes from cy- bersecurity texts,","venue":null,"work_id":"14199c58-d7aa-4b77-a52a-5d0639ab49c6","year":2019},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.750451Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:ddd0fdc53c3da2de661a51ac91a3ac9d5bed8ceea668fc966f3c35af758351ac","observation_id":"36623d0f-61e1-4384-b308-e517d9db2080","resolution":{"observed_at":"2026-08-12T11:59:23.915070Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.901566Z","title":"Team Error Point at BLP-2023 Task 2: A Comparative Exploration of Hybrid Deep Learning and Machine Learning Approach for Advanced Sentiment Analysis Techniques,","venue":null,"work_id":"56a5c71f-573b-42c0-863c-3bd5abad2bb8","year":2023},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.753304Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:793c16cd8a12d20bca03c2703b485639b3f20ccbf1672059d2278d011e4445e0","observation_id":"cd6dc117-3ba0-43d7-ab5b-a0ddafe908c0","resolution":{"observed_at":"2026-08-12T11:59:23.904901Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.892768Z","title":"Learning a deep hybrid model for semi-supervised text classification,","venue":null,"work_id":"4e888a61-0739-4b0b-a813-98916f8f32fe","year":2015},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.756187Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:6fffe71139df4539000cd9496856262595bc6131eea6856fb02b34461f51ba31","observation_id":"4411dbc2-6a91-42e8-a66e-8a1c81b2bb69","resolution":{"observed_at":"2026-08-12T11:59:23.895987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1710.00164","last_updated":"2017-09-30T08:46:03Z","snapshot_observed_at":"2026-08-03T21:52:07.172373Z","submitted_at":"2017-09-30T08:46:03Z","title":"Speaker Role Contextual Modeling for Language Understanding and Dialogue Policy Learning","version":1},"cited_work":{"arxiv_id":"1710.00164","doi":null,"metadata_source":"pith","pith_arxiv_id":"1710.00164","snapshot_observed_at":"2026-08-12T11:59:23.660436Z","title":"Speaker Role Contextual Modeling for Language Understanding and Dialogue Policy Learning","venue":"cs.CL","work_id":"26710d10-ffdf-408a-8563-cd7004a85231","year":2017},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.759089Z"},"links":{"cited_paper":"/paper/1710.00164","citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:c2b774d14281f14e835947545030664c0a8b0a6515b0fa8d4f90f7bb249aa11a","observation_id":"4e936e48-f244-4da2-8b7a-ddb0a925168c","resolution":{"observed_at":"2026-08-12T11:59:23.664045Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.18657","last_updated":"2023-05-31T22:50:25Z","snapshot_observed_at":"2026-08-05T00:59:26.804256Z","submitted_at":"2023-05-29T23:44:26Z","title":"Representation Of Lexical Stylistic Features In Language Models' Embedding Space","version":2},"cited_work":{"arxiv_id":"2305.18657","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.18657","snapshot_observed_at":"2026-08-12T11:59:23.648982Z","title":"Representation Of Lexical Stylistic Features In Language Models' Embedding Space","venue":"cs.CL","work_id":"14ee90bc-44ff-4c41-81cf-d887aa4e9301","year":2023},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.762399Z"},"links":{"cited_paper":"/paper/2305.18657","citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:93f9fa7b0f53fdf034b81c42652bc0e3b3cad6e9b45601b487c9ca2327c1b0f5","observation_id":"9c6a53ed-261c-4ace-beb3-d8f314950969","resolution":{"observed_at":"2026-08-12T11:59:23.652548Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"6454.17645","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:23.634398Z","title":"What’s in a region? or computing control dependence regions in near-linear time for reducible control flow,","venue":null,"work_id":"9cf5fc84-8f2c-4d1a-8439-d3fad795c44b","year":1993},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.765880Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:76d9bac6b52e579ff1331ff55731ca902e5400f43de37210bbe84156b78fbc99","observation_id":"4d752b04-7ed6-43ec-81bd-758707007eb4","resolution":{"observed_at":"2026-08-12T11:59:23.639155Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.883748Z","title":"LLM Knows Body Language, Too: Translating Speech V oices into Human Gestures,","venue":null,"work_id":"8943821f-aac4-4c56-9b5d-4eed3d0c9e82","year":2024},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.768764Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:9e39ec85e53e095cf8ee947b3467150067cdc81da50aa4b66d01a9f74e0abbcb","observation_id":"8eef1b06-7f88-479a-87af-ff1f6a53555a","resolution":{"observed_at":"2026-08-12T11:59:23.887287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.875095Z","title":"Efficient deep features learning for vulnerability detection using character n-gram embedding,","venue":null,"work_id":"e4a117ce-c0d9-4eec-a326-24aa93e59111","year":2021},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.771553Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:c8735136a011ebda6060adbcd37eb5462b811eabe2d9434d3ac8185eef30e8a5","observation_id":"cb4e5d43-0097-468e-8c47-fab8dde35058","resolution":{"observed_at":"2026-08-12T11:59:23.878465Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2225.23722","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:23.542897Z","title":"Software Vul- nerability Prediction using Text Analysis Techniques,","venue":null,"work_id":"43518001-7db2-42cb-b7a3-05c26c383ffe","year":2012},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.774443Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:a0d9b9eaa6be4c591b063b746ad8e5c0699e17b629e9ee833c295362cd4240a2","observation_id":"2f0acfde-c8f2-4abf-895d-8f3416c2f808","resolution":{"observed_at":"2026-08-12T11:59:23.548185Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2007.43855","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:23.472491Z","title":"A multivariate analysis of static code attributes for defect prediction,","venue":null,"work_id":"ddd729e4-e837-4f88-ae08-e17b91a9fd7c","year":2007},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.777375Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:adc69bae878d75ede68181657188fb601151badade72b62d01e472d9660ced13","observation_id":"493ee3cc-d77f-4b9a-85d0-23987f983458","resolution":{"observed_at":"2026-08-12T11:59:23.477273Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:22.780293Z","title":"VulSlicer: Vulnerability detection through code slicing,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.780293Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:4408efdfd656a8437acf9b8b6055cfe43d27a6351d653f5ca7b755adbc5bf029","observation_id":"70c699fc-7c08-45c3-9007-296444c2d83e","resolution":{"observed_at":"2026-08-12T11:59:22.780293Z","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":"2026-08-12T11:59:23.866873Z","title":"SlicedLocator: Code vulnerability locator based on sliced dependence graph,","venue":null,"work_id":"6f02221f-eda2-46be-937a-f585aeb81f44","year":2023},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.783259Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:17df41a63c4ec115dac1bffa3006b8d4bb9d8787274796c770e041fd03850988","observation_id":"ff994995-df16-4eeb-a894-e8671650950c","resolution":{"observed_at":"2026-08-12T11:59:23.869934Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1909.03496","last_updated":"2019-09-08T16:14:31Z","snapshot_observed_at":"2026-08-09T15:14:45.070830Z","submitted_at":"2019-09-08T16:14:31Z","title":"Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.03496","snapshot_observed_at":"2026-08-12T11:59:22.786305Z","title":"Devign: Effective Vulnera- bility Identification by Learning Comprehensive Program Semantics via Graph Neural Networks,","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.786305Z"},"links":{"cited_paper":"/paper/1909.03496","citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:88b8c70f2f959e697afabdc9b07ae66da66f061608c3103dad9c28b35482dd6a","observation_id":"d16978f8-b6c2-4448-8659-fea1dd334f9b","resolution":{"observed_at":"2026-08-12T11:59:22.786305Z","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":"2026-08-12T11:59:22.789791Z","title":"V2W- BERT: A Framework for Effective Hierarchical Multiclass Classification of Software Vulnerabilities,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.789791Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:f8bb611456570db53fc1ff259ce6a7a3677a7da37ce71c9d4c0faa18ac867970","observation_id":"27d87904-2b19-4df6-a9dc-7be9e57e9d06","resolution":{"observed_at":"2026-08-12T11:59:22.789791Z","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":"10.3390/app9194086","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:22.933533Z","title":"Instruction2vec: Efficient Preprocessor of Assembly Code to Detect Software Weakness with CNN,","venue":null,"work_id":"cc9127bb-a48a-4adc-a759-796c2c56a03a","year":2019},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.792826Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:d749b7b5629b14d61b0af6fd719d600f754e422574e4fdda79fc881486a78126","observation_id":"d60452a3-347a-40da-87c6-b8d113627988","resolution":{"observed_at":"2026-08-12T11:59:22.937107Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.858662Z","title":"Boosting coverage-based fault localization via graph-based representation learning,","venue":null,"work_id":"cc1101eb-e584-4f48-9dc2-00018141b23a","year":2021},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.795927Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:ce0b21d03a35ab53bde638c19a5ce0e7ede205077eda4713fdcf7e3b2eb11a86","observation_id":"73115c7c-f0b1-4c06-af98-cadd49903394","resolution":{"observed_at":"2026-08-12T11:59:23.861739Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.850228Z","title":"Combining deep learning with information retrieval to localize buggy files for bug reports (n),","venue":null,"work_id":"e75e95fe-e21c-41f4-841f-c37d1eb3443a","year":2015},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.798986Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:cb78c09bb248d4960aee4cc452566f969c074a48bb75e144294963b11881bd5c","observation_id":"cae0d0f2-102f-436a-8fd0-daaa7d4aeac8","resolution":{"observed_at":"2026-08-12T11:59:23.853487Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.842095Z","title":"DeepFL: integrating multiple fault diagnosis dimensions for deep fault localization,","venue":null,"work_id":"4a77d393-064e-4b02-9359-2811f4e2a2cd","year":2019},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.801877Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:c786894180dbd1428e4fa51575abb38f81c78c4dea4239159f651f853e09ade2","observation_id":"497cd5a2-db1c-4baf-8f4b-3254df845718","resolution":{"observed_at":"2026-08-12T11:59:23.845259Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.833565Z","title":"Fault localization with code coverage representation learning,","venue":null,"work_id":"f9aa8086-646d-4628-8587-a80f2d3dfc43","year":2021},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.804777Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:24d01d52b69a6b7c46021eb6431eabf50108e3d284cd15dde3e2468cf8ac7ef1","observation_id":"9811c20e-ba30-4aec-814f-38ba4f9ef11a","resolution":{"observed_at":"2026-08-12T11:59:23.836891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.824959Z","title":"GraphCodeBERT: Pre-training Code Representations with Data Flow,","venue":null,"work_id":"242d3ce6-041a-4f1a-834d-b76cb199cc98","year":2021},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.807732Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:3d62ca4120d39d8e7a6e1874271ff898fbe740abbeb77bae2600bbeb77fc7024","observation_id":"02a3d9bd-f896-47c8-8ded-39a7d66b67b0","resolution":{"observed_at":"2026-08-12T11:59:23.828148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2002.08155","last_updated":"2020-09-18T15:38:12Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-02-19T13:09:07Z","title":"CodeBERT: A Pre-Trained Model for Programming and Natural Languages","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.08155","snapshot_observed_at":"2026-08-12T11:59:22.810822Z","title":"CodeBERT: A pre-trained model for programming and natural languages,","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.810822Z"},"links":{"cited_paper":"/paper/2002.08155","citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:4695482c37f7bb98ce58ad2c7b4ea0c85e5f37ce426485dd9e9638cf31fdf975","observation_id":"4e3e1997-c038-4647-a216-37242cf6cda0","resolution":{"observed_at":"2026-08-12T11:59:22.810822Z","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":"2026-08-12T11:59:22.814064Z","title":"LineVul: a transformer-based line- level vulnerability prediction,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.814064Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:6007c5b2ddc14bf419446fbe3cc147ae96040bd77294bd1636b01d0d28442dc6","observation_id":"46c10e91-bc44-4af6-934d-9793714a5deb","resolution":{"observed_at":"2026-08-12T11:59:22.814064Z","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":"10.1007/s10664-023-10346-3","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:22.924664Z","title":"AIBugHunter: A Practi- cal tool for predicting, classifying and repairing software vulnerabili- ties,","venue":null,"work_id":"b77f8d34-b315-4fee-9d80-d9b73b99ee1a","year":2024},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.817129Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:5d9704579459b913c46f97fe3024e2d236f2540ae2f6a42a7649539489edb142","observation_id":"44d842a5-82e9-4d8a-a6fb-425486de75b8","resolution":{"observed_at":"2026-08-12T11:59:22.928048Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.816843Z","title":"Draper VDISC Dataset- Vulnerability Detection in Source Code","venue":null,"work_id":"121abc77-86d1-44eb-a214-e400b878446a","year":2024},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.820124Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:e95c2fe33f804b9321ed9a9d05dfb18e971dcd220023baa4d9e3d51509f953f4","observation_id":"1730aeda-ee64-47dc-b2c0-407f672f495b","resolution":{"observed_at":"2026-08-12T11:59:23.819996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.technovation.2017.01.001","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:22.916030Z","title":"and Park, Y","venue":null,"work_id":"9af820b2-6d0e-4d21-9e9a-6d91930105c6","year":2017},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.822874Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:6c2b9a8d9f22ac3c0aefd7c9349fd560a8fce553fdba26290869bd744f39a7e0","observation_id":"d3b13680-15bf-498c-9969-293a649f24c2","resolution":{"observed_at":"2026-08-12T11:59:22.919343Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.808133Z","title":"and Li, C.H","venue":null,"work_id":"db1ebf03-38e2-435a-bc1a-694ec138f466","year":2008},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.825935Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:bd2e1a1930e226aedbec6c056c7011c79f571650b422ba5487dd9cfc9d4d9ee6","observation_id":"501850da-c74b-4808-babc-7df9e0179cc2","resolution":{"observed_at":"2026-08-12T11:59:23.811215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.799971Z","title":"and Pan, Y .T","venue":null,"work_id":"8475a5a4-a9c6-4a57-b63a-2bbdd3b5cf56","year":2021},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.828918Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:43e6885f649ad75158fa89f56acd5f850538d4e21c3a699f03333fcf087822c0","observation_id":"ae3abd2f-98f5-425f-8c71-5eb496d873fb","resolution":{"observed_at":"2026-08-12T11:59:23.802912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1612.03651","last_updated":"2016-12-12T12:51:03Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2016-12-12T12:51:03Z","title":"FastText.zip: Compressing text classification models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1612.03651","snapshot_observed_at":"2026-08-12T11:59:22.831851Z","title":"and Mikolov, T","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.831851Z"},"links":{"cited_paper":"/paper/1612.03651","citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:9c63ac37ecf844d87e1f4c14353799e381de19fca52cdc6f7523c2e847efd9bd","observation_id":"3025c91a-10c3-4814-a0bf-c5655a3a0e61","resolution":{"observed_at":"2026-08-12T11:59:22.831851Z","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":"2026-08-12T11:59:23.791081Z","title":"and Wu, H","venue":null,"work_id":"883eca04-32df-4eeb-9f74-08d5cba6ab8a","year":2018},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.834994Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:b3417a444b34a5b56a6c1b065eac6d7ab7197175ac1d1b53f093d3b33dc014cd","observation_id":"f944946b-7b59-4ab2-9fbd-eca1bbd6115a","resolution":{"observed_at":"2026-08-12T11:59:23.794136Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.782067Z","title":"and Manning, C.D., 2014, October","venue":null,"work_id":"09a95b33-26b4-4fce-854b-31078b03c221","year":2014},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.838227Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:0ab0cf305868e04c09184ef86885d57696605c75ce9cd14cefa50f523f2fa7e2","observation_id":"030bd07e-75d4-4a0e-8c19-63da96bb6008","resolution":{"observed_at":"2026-08-12T11:59:23.785668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.773387Z","title":"and Sivakumar, S., 2022","venue":null,"work_id":"970742a0-c227-4a66-a34d-ffdcc8a30390","year":2022},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.841309Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:16b4725c78028f9b098f0b862d0c6d5dd4beb94be00925a5c7b1d21f95c027b7","observation_id":"78eff4d4-eb6a-48f2-b495-0301f3136ccd","resolution":{"observed_at":"2026-08-12T11:59:23.776683Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.762984Z","title":"Stochastic gradient descent classifier-based lightweight intrusion detection systems using the efficient feature subsets of datasets,","venue":null,"work_id":"34a7fb13-0a74-4594-a12c-eca0d689b95e","year":null},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.844047Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:4fd9558b1c5294d918115a4cdf020ac4e9e378aa81de81664cd44aa6b6d8b670","observation_id":"aed68b73-c738-4a0a-8b84-f5fb13620d03","resolution":{"observed_at":"2026-08-12T11:59:23.767073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2409.08925","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:23.156002Z","title":"Multi forests: Variable importance for multi-class outcomes,","venue":null,"work_id":"f46a5c2b-6cd4-4ea9-a0b0-b02a4dab63d9","year":2024},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.848036Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:f1a219ec28e628ba07cdfe59ee2e90ded2f2a2f2e1260baea6e184b88319c0c4","observation_id":"1f67772a-1039-44e9-9ea1-4c25a29cf17a","resolution":{"observed_at":"2026-08-12T11:59:23.160637Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/math9070751","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:22.906941Z","title":"A consolidated decision tree-based intrusion detection system for binary and multiclass imbalanced datasets,","venue":null,"work_id":"e0201354-1156-4a9d-b4cc-fa5657cd04fe","year":2021},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.850973Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:431c43a1dfe7c0e140539523d3a5e9d0517f1ab9aaa60dfb0798d113ed362844","observation_id":"9a199766-e97c-49d5-9b05-08710c090284","resolution":{"observed_at":"2026-08-12T11:59:22.910090Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.754160Z","title":"Identifying domain independent update intents in task based dialogs,","venue":null,"work_id":"dffdfc9d-a6ef-49fd-8969-9f318f879bb0","year":2018},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.854050Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:026d299799e826162d9d2a16cc79e9220505c88848ccba0517e05eaffac5c555","observation_id":"3df57dfb-a576-4aeb-94da-0cdc3067a476","resolution":{"observed_at":"2026-08-12T11:59:23.757289Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16584","last_updated":"2024-05-26T14:27:48Z","snapshot_observed_at":"2026-08-12T23:57:45.692617Z","submitted_at":"2024-05-26T14:27:48Z","title":"MentalManip: A Dataset For Fine-grained Analysis of Mental Manipulation in Conversations","version":1},"cited_work":{"arxiv_id":"2405.16584","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.16584","snapshot_observed_at":"2026-08-12T11:59:23.086738Z","title":"MentalManip: A Dataset For Fine-grained Analysis of Mental Manipulation in Conversations","venue":"cs.CL","work_id":"a0262e2f-8f7d-4385-8a1a-a8ae7f7abbf0","year":2024},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.856942Z"},"links":{"cited_paper":"/paper/2405.16584","citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:c19910f66744ffbc65a9967c1ef44cca0e93352d3fec33270482d261ad2527ee","observation_id":"3c9fa594-0900-4304-92a2-09e5ba3fd10d","resolution":{"observed_at":"2026-08-12T11:59:23.091460Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.743697Z","title":"Why Should I Trust You? Explaining the Predictions of Any Classifier,","venue":null,"work_id":"18b59ce2-3e97-4a7c-a075-d668ca38a86d","year":2016},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.861290Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:778fe1c2c0a00707e937f5c6204952a009122e552c4ee015391b2e940243a3fd","observation_id":"21205b61-2a80-468a-ada7-9097412359d6","resolution":{"observed_at":"2026-08-12T11:59:23.747764Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"questions/2991052","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:23.073866Z","title":"Why is this code vulnerable to buffer overflow attacks?,","venue":null,"work_id":"b9dd6e9f-fb4f-4525-a153-ad9226ffcf5a","year":2024},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.864557Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:e3848a9b14c44934e044b1d5ca4dcb3faf96de4a37e27cfe2187e2ecef1e277c","observation_id":"9108cee2-ff51-470d-a1a6-29b456b595ae","resolution":{"observed_at":"2026-08-12T11:59:23.079247Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s00521-024-09819-3","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:22.895688Z","title":"Multi-class vulnerability prediction using value flow and graph neural networks,","venue":null,"work_id":"3da7e5d6-3568-4f9b-85cf-6e255c61baa7","year":2024},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.867471Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:b0606cfddbbe947ce04927b5fe70152aca3e20bb88a84a9810ce72189f7090ac","observation_id":"f83a773e-770b-461e-b700-e0ca1ad9b88f","resolution":{"observed_at":"2026-08-12T11:59:22.900689Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"records/1405818","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:59:23.000770Z","title":"CodeGraphNet,","venue":null,"work_id":"7e0bb422-09cd-4574-bbdb-9e7b593d1549","year":2024},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.870551Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:11afe09413eb76ef302af79d37197075e8c2a23bf243b0490a273eb3a978dac6","observation_id":"73858206-524b-4b33-ba15-76be96527301","resolution":{"observed_at":"2026-08-12T11:59:23.007468Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T11:59:23.956723Z","title":"Available: https://www.k2io.com/the-final-count- vulnerabilities-up-almost-10-in-2021/","venue":null,"work_id":"3f7ae32e-517a-4d8e-ac1c-b5a597ef39f0","year":2021},"citing_paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification","version":2},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-12T11:59:22.731052Z"},"links":{"citing_paper":"/paper/2411.17621"},"observation_digest":"sha256:91b677ea80399a85ad24cc87a8a8aa308970e6335f95df2f105ddafb64294d50","observation_id":"0572e2ea-2461-4010-b435-86f57357092a","resolution":{"observed_at":"2026-08-12T11:59:23.959897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.17621","last_updated":"2024-11-27T17:18:36Z","latest_version":2,"primary_category":"cs.SE","snapshot_observed_at":"2026-08-12T11:52:36.655939Z","submitted_at":"2024-11-26T17:33:02Z","title":"A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":0,"metadata_mismatch":4,"parse_uncertain":0,"unresolved":7,"verified_exact":11,"verified_fuzzy":25},"total_outbound_references":47},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2411.17621."}