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Paper Citation Record · LEDGER

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification

As of 14 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2411.17621.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.17621 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:59:22.870551Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

  • verified exact11
  • verified fuzzy25
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2343db7e-178a-4a47-8bb2-a7e9d32587fa · outbound

This paper cites an unresolved cited work.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-12T11:59:23.968268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f19cd2b1-6dd7-448e-b5f2-75b96fc0b567 · outbound

This paper cites Buffer overflow vulnerabilities and attacks explained,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Buffer overflow vulnerabilities and attacks explained,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.951572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.734263Z digest=sha256:4e804dda0878c72681f59367811059329551f698149ab8926b921eb54bbca7b1

Observation 071d62fa-2435-4bf7-ad85-abaa2bc1bceb · outbound

This paper cites Internet Crime Report,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Internet Crime Report,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.942711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.737460Z digest=sha256:390d27f367240409b71d6ff2630817935d76c9e4213ee7c278bb34cffe28c79e

Observation a5ff1989-0363-4ea5-a70b-40f4626dc5fb · outbound

This paper cites 533 million Facebook users’ phone numbers and personal data have been leaked online,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification 533 million Facebook users’ phone numbers and personal data have been leaked online,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.934373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.740875Z digest=sha256:af2c4605803c54802aa263f5c5172311005c6c5917326746b2a6d1e3fd0cb357

Observation e1e18fe2-2fc9-4aa4-827d-649bfb603718 · outbound

This paper cites Multiclass Classification of Software Vulnerabilities with Deep Learning,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Multiclass Classification of Software Vulnerabilities with Deep Learning,

Reference 5

Resolution
metadata mismatch
raw_fallback, observed 2026-08-12T11:59:23.738088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.744085Z digest=sha256:7e293d385e77ea3c99cce610952f20159b486441de23d77381a4a8a49676d85f

Observation 5141802c-d3cc-497c-8c0f-6b1102d14341 · outbound

This paper cites VMware Flaw a Vector in SolarWinds Breach?,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification VMware Flaw a Vector in SolarWinds Breach?,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.924755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.747325Z digest=sha256:b2f1103babbdef146ab902eb14f65d7dd028eb508b817b9c5d319e3a1f756095

Observation 36623d0f-61e1-4384-b308-e517d9db2080 · outbound

This paper cites Predicting malware attributes from cy- bersecurity texts,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Predicting malware attributes from cy- bersecurity texts,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.915070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.750451Z digest=sha256:ee7aa6f6663b95ba439096160f5e99a926468f66822e462aaeac0cb7cb11718d

Observation cd6dc117-3ba0-43d7-ab5b-a0ddafe908c0 · outbound

This paper cites Team Error Point at BLP-2023 Task 2: A Comparative Exploration of Hybrid Deep Learning and Machine Learning Approach for Advanced Sentiment Analysis Techniques,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Team Error Point at BLP-2023 Task 2: A Comparative Exploration of Hybrid Deep Learning and Machine Learning Approach for Advanced Sentiment Analysis Techniques,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.904901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.753304Z digest=sha256:2092e5d5fb16be3d9414d8041f4e8d086ed39e12dbb5a755c5abd65b89a0313f

Observation 4411dbc2-6a91-42e8-a66e-8a1c81b2bb69 · outbound

This paper cites Learning a deep hybrid model for semi-supervised text classification,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Learning a deep hybrid model for semi-supervised text classification,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.895987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.756187Z digest=sha256:92bf218aa7b16b068ea4a8fc42aa3aeff1bd2bf22d1f924014cf1b72401da5e6

Observation 4e936e48-f244-4da2-8b7a-ddb0a925168c · outbound

This paper cites Speaker Role Contextual Modeling for Language Understanding and Dialogue Policy Learning.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Speaker Role Contextual Modeling for Language Understanding and Dialogue Policy Learning

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-12T11:59:23.664045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.759089Z digest=sha256:b6a56254472c452cb32233e37553e46de5fc7341240fada08859f87c139f20ed

Observation 9c6a53ed-261c-4ace-beb3-d8f314950969 · outbound

This paper cites Representation Of Lexical Stylistic Features In Language Models' Embedding Space.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Representation Of Lexical Stylistic Features In Language Models' Embedding Space

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-12T11:59:23.652548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.762399Z digest=sha256:9d26e50f76dbc359e11da9ca6d3d72d22ea11eff75a3ed7abd75cc104b6af731

Observation 4d752b04-7ed6-43ec-81bd-758707007eb4 · outbound

This paper cites What’s in a region? or computing control dependence regions in near-linear time for reducible control flow,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification What’s in a region? or computing control dependence regions in near-linear time for reducible control flow,

Reference 12

Resolution
metadata mismatch
raw_fallback, observed 2026-08-12T11:59:23.639155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.765880Z digest=sha256:582be88ce6c30918c9a492baae428ef37acd204c4a90a6041605a89c957434b5

Observation 8eef1b06-7f88-479a-87af-ff1f6a53555a · outbound

This paper cites LLM Knows Body Language, Too: Translating Speech V oices into Human Gestures,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification LLM Knows Body Language, Too: Translating Speech V oices into Human Gestures,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.887287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.768764Z digest=sha256:a95a9b31b652fecf7db0fda1529128626be567f11d18bde333457be83e7a1fea

Observation cb4e5d43-0097-468e-8c47-fab8dde35058 · outbound

This paper cites Efficient deep features learning for vulnerability detection using character n-gram embedding,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Efficient deep features learning for vulnerability detection using character n-gram embedding,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.878465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.771553Z digest=sha256:c31fc02950479564e06015f1fb2169a2f9810518acff4a06ba412afa6c771668

Observation 2f0acfde-c8f2-4abf-895d-8f3416c2f808 · outbound

This paper cites Software Vul- nerability Prediction using Text Analysis Techniques,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Software Vul- nerability Prediction using Text Analysis Techniques,

Reference 15

Resolution
metadata mismatch
raw_fallback, observed 2026-08-12T11:59:23.548185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.774443Z digest=sha256:06335a794d92f727dfbf028a96fc610707301912ba192858268d1dfb16d83092

Observation 493ee3cc-d77f-4b9a-85d0-23987f983458 · outbound

This paper cites A multivariate analysis of static code attributes for defect prediction,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification A multivariate analysis of static code attributes for defect prediction,

Reference 16

Resolution
metadata mismatch
raw_fallback, observed 2026-08-12T11:59:23.477273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.777375Z digest=sha256:64deb0ebf61c0c1a9e22b0fd27615ef91ceec9f3ae70e7d13404372d559ec887

Observation 70c699fc-7c08-45c3-9007-296444c2d83e · outbound

This paper cites VulSlicer: Vulnerability detection through code slicing,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification VulSlicer: Vulnerability detection through code slicing,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-12T11:59:22.780293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:59:22.780293Z digest=sha256:065a9679355b579dee36c10984d08d973038c3a3999926a710119e7154273d89

Observation ff994995-df16-4eeb-a894-e8671650950c · outbound

This paper cites SlicedLocator: Code vulnerability locator based on sliced dependence graph,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification SlicedLocator: Code vulnerability locator based on sliced dependence graph,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.869934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.783259Z digest=sha256:1dce7005a89feb9e75efa9709d46508ad279c822949c63bf7849676a0d0c54d1

Observation d16978f8-b6c2-4448-8659-fea1dd334f9b · outbound

This paper cites Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-12T11:59:22.786305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:59:22.786305Z digest=sha256:326abff00538c76ec3304195538e796a53a7293822d037bb126a5ad88de497da

Observation 27d87904-2b19-4df6-a9dc-7be9e57e9d06 · outbound

This paper cites V2W- BERT: A Framework for Effective Hierarchical Multiclass Classification of Software Vulnerabilities,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification V2W- BERT: A Framework for Effective Hierarchical Multiclass Classification of Software Vulnerabilities,

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-12T11:59:22.789791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:59:22.789791Z digest=sha256:7378269adb2f4567a6ced87724d388fd06770b7b504cb2c1ffed118847cb55cf

Observation d60452a3-347a-40da-87c6-b8d113627988 · outbound

This paper cites Instruction2vec: Efficient Preprocessor of Assembly Code to Detect Software Weakness with CNN,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Instruction2vec: Efficient Preprocessor of Assembly Code to Detect Software Weakness with CNN,

Reference 21

Resolution
verified exact
doi, observed 2026-08-12T11:59:22.937107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.792826Z digest=sha256:457df1a79100cfd9407788479ff9f56f17f7c6b33624777ec4ca10ca2267e864

Observation 73115c7c-f0b1-4c06-af98-cadd49903394 · outbound

This paper cites Boosting coverage-based fault localization via graph-based representation learning,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Boosting coverage-based fault localization via graph-based representation learning,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.861739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.795927Z digest=sha256:e5a28081986f3dd63d1944f4b0288b9ab931eca092cfdb4d9f6c0687fb7cbc9f

Observation cae0d0f2-102f-436a-8fd0-daaa7d4aeac8 · outbound

This paper cites Combining deep learning with information retrieval to localize buggy files for bug reports (n),.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Combining deep learning with information retrieval to localize buggy files for bug reports (n),

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.853487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.798986Z digest=sha256:51475164661bc86982cea7cec616f1961995ff4aaeab1313ba60241321580929

Observation 497cd5a2-db1c-4baf-8f4b-3254df845718 · outbound

This paper cites DeepFL: integrating multiple fault diagnosis dimensions for deep fault localization,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification DeepFL: integrating multiple fault diagnosis dimensions for deep fault localization,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.845259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.801877Z digest=sha256:768d484ddab6efb149237576d41409e0773db2b0fa86122bf046bfd82708ae04

Observation 9811c20e-ba30-4aec-814f-38ba4f9ef11a · outbound

This paper cites Fault localization with code coverage representation learning,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Fault localization with code coverage representation learning,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.836891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.804777Z digest=sha256:1005aaa3054316e94f81f0008c1af0b014bffd0e42ec58d864b8f6e60e7571e2

Observation 02a3d9bd-f896-47c8-8ded-39a7d66b67b0 · outbound

This paper cites GraphCodeBERT: Pre-training Code Representations with Data Flow,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification GraphCodeBERT: Pre-training Code Representations with Data Flow,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.828148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.807732Z digest=sha256:e72dd94e583972baa162ebcc3b95382999bcfa9d535ec5516d09d3cf4fa36c0f

Observation 4e3e1997-c038-4647-a216-37242cf6cda0 · outbound

This paper cites CodeBERT: A Pre-Trained Model for Programming and Natural Languages.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification CodeBERT: A Pre-Trained Model for Programming and Natural Languages

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-12T11:59:22.810822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:59:22.810822Z digest=sha256:9da5dde4c206c7a843ee2a106d58f75accd7fe12648fc25a92739bdee2fd8e49

Observation 46c10e91-bc44-4af6-934d-9793714a5deb · outbound

This paper cites LineVul: a transformer-based line- level vulnerability prediction,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification LineVul: a transformer-based line- level vulnerability prediction,

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-12T11:59:22.814064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:59:22.814064Z digest=sha256:338dcf73bebc8deecfd9aa23ffeea27fbce18293e8cc2e28b88efd7b1b6ac503

Observation 44d842a5-82e9-4d8a-a6fb-425486de75b8 · outbound

This paper cites AIBugHunter: A Practi- cal tool for predicting, classifying and repairing software vulnerabili- ties,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification AIBugHunter: A Practi- cal tool for predicting, classifying and repairing software vulnerabili- ties,

Reference 29

Resolution
verified exact
doi, observed 2026-08-12T11:59:22.928048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.817129Z digest=sha256:c7a850b3102d062a0bbf3ac9091d622a199f628c091b7c6b833e6cb859abe498

Observation 1730aeda-ee64-47dc-b2c0-407f672f495b · outbound

This paper cites Draper VDISC Dataset- Vulnerability Detection in Source Code.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Draper VDISC Dataset- Vulnerability Detection in Source Code

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.819996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.820124Z digest=sha256:2804712f4d692e110ea0acc7d54e57cfca32604b935c0938f5069d9fb7b36ba3

Observation d3b13680-15bf-498c-9969-293a649f24c2 · outbound

This paper cites and Park, Y.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification and Park, Y

Reference 31

Resolution
verified exact
doi, observed 2026-08-12T11:59:22.919343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.822874Z digest=sha256:2a51ecef823936cbef8dd9aca881e845ee535e9b8fd14be7e355814010cb9ca1

Observation 501850da-c74b-4808-babc-7df9e0179cc2 · outbound

This paper cites and Li, C.H.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification and Li, C.H

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.811215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.825935Z digest=sha256:ebfbd0a79637e7daf06e63bdadc750f87562ae99e8c563f0e090e798c6466d4f

Observation ae3abd2f-98f5-425f-8c71-5eb496d873fb · outbound

This paper cites and Pan, Y .T.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification and Pan, Y .T

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.802912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.828918Z digest=sha256:4e4625b070f6532a6c8334ee9735f714238c39c744104c79e983e96cfb5486fa

Observation 3025c91a-10c3-4814-a0bf-c5655a3a0e61 · outbound

This paper cites FastText.zip: Compressing text classification models.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification FastText.zip: Compressing text classification models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-12T11:59:22.831851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:59:22.831851Z digest=sha256:40a832f52bbc8971300c53cd1028765fe3232ba29ede1cb66fbb190da5ffb638

Observation f944946b-7b59-4ab2-9fbd-eca1bbd6115a · outbound

This paper cites and Wu, H.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification and Wu, H

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.794136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.834994Z digest=sha256:9f9422aecebeb140ac2f3662074f5b53c3d71d152a640c75f836aad5c66657e6

Observation 030bd07e-75d4-4a0e-8c19-63da96bb6008 · outbound

This paper cites and Manning, C.D., 2014, October.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification and Manning, C.D., 2014, October

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.785668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.838227Z digest=sha256:d960e62f6b591812cf7566fb7d19bdf8ee903eb8e62cea9c95b2196362e5ff90

Observation 78eff4d4-eb6a-48f2-b495-0301f3136ccd · outbound

This paper cites and Sivakumar, S., 2022.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification and Sivakumar, S., 2022

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.776683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.841309Z digest=sha256:cf28bd77982fc6eefd8244d5ae69387e17fbcc7be1b292557cfed6f448afd02c

Observation aed68b73-c738-4a0a-8b84-f5fb13620d03 · outbound

This paper cites Stochastic gradient descent classifier-based lightweight intrusion detection systems using the efficient feature subsets of datasets,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Stochastic gradient descent classifier-based lightweight intrusion detection systems using the efficient feature subsets of datasets,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.767073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.844047Z digest=sha256:dab52c6db273cd5e60691d0bbe4defcd12bb2bc81b767e15093959085c455d73

Observation 1f67772a-1039-44e9-9ea1-4c25a29cf17a · outbound

This paper cites Multi forests: Variable importance for multi-class outcomes,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Multi forests: Variable importance for multi-class outcomes,

Reference 39

Resolution
verified exact
raw_fallback, observed 2026-08-12T11:59:23.160637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.848036Z digest=sha256:d105d55e5ae9619380eb270ab6511369e0b236e051f5424a9f0cc4ba026f5ccc

Observation 9a199766-e97c-49d5-9b05-08710c090284 · outbound

This paper cites A consolidated decision tree-based intrusion detection system for binary and multiclass imbalanced datasets,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification A consolidated decision tree-based intrusion detection system for binary and multiclass imbalanced datasets,

Reference 40

Resolution
verified exact
doi, observed 2026-08-12T11:59:22.910090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.850973Z digest=sha256:eefbb543b3f6b5e2448ca74408bb86b4f42b42d4176301572cd2ee429ffedd29

Observation 3df57dfb-a576-4aeb-94da-0cdc3067a476 · outbound

This paper cites Identifying domain independent update intents in task based dialogs,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Identifying domain independent update intents in task based dialogs,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.757289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.854050Z digest=sha256:4289a46247646473c356ba42728c7f71754d152016d87aad2cbb0b0bd1224f30

Observation 3c9fa594-0900-4304-92a2-09e5ba3fd10d · outbound

This paper cites MentalManip: A Dataset For Fine-grained Analysis of Mental Manipulation in Conversations.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification MentalManip: A Dataset For Fine-grained Analysis of Mental Manipulation in Conversations

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-12T11:59:23.091460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.856942Z digest=sha256:8a6246741c8cbb62018fa7002c280fe11a9b66fb16b65845d3de6c1e17b72abd

Observation 21205b61-2a80-468a-ada7-9097412359d6 · outbound

This paper cites Why Should I Trust You? Explaining the Predictions of Any Classifier,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Why Should I Trust You? Explaining the Predictions of Any Classifier,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.747764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.861290Z digest=sha256:454643ac37e1f36e6f22fff1683b2b17312c547dc8ebb2054b2c65aee85e6220

Observation 9108cee2-ff51-470d-a1a6-29b456b595ae · outbound

This paper cites Why is this code vulnerable to buffer overflow attacks?,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Why is this code vulnerable to buffer overflow attacks?,

Reference 44

Resolution
verified exact
raw_fallback, observed 2026-08-12T11:59:23.079247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.864557Z digest=sha256:d0cddcc434357ba8f77b02969e534719c8b61d8f53d08ba60cea2e02ebb5c23f

Observation f83a773e-770b-461e-b700-e0ca1ad9b88f · outbound

This paper cites Multi-class vulnerability prediction using value flow and graph neural networks,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Multi-class vulnerability prediction using value flow and graph neural networks,

Reference 45

Resolution
verified exact
doi, observed 2026-08-12T11:59:22.900689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.867471Z digest=sha256:fb6adcbe77890ac809d420046fc9daa46a444aea2210ec3d83a1fbb7f4084f0e

Observation 73858206-524b-4b33-ba15-76be96527301 · outbound

This paper cites CodeGraphNet,.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification CodeGraphNet,

Reference 46

Resolution
verified exact
raw_fallback, observed 2026-08-12T11:59:23.007468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.870551Z digest=sha256:eb00a71882ba2d887753011e197a25cf5ad4c88c812c42ff93e4336eb6993fa9

Observation 0572e2ea-2461-4010-b435-86f57357092a · outbound

This paper cites Available: https://www.k2io.com/the-final-count- vulnerabilities-up-almost-10-in-2021/.

A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification Available: https://www.k2io.com/the-final-count- vulnerabilities-up-almost-10-in-2021/

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:59:23.959897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T11:59:22.731052Z digest=sha256:f3c118cb73d5068d627bcf63dd4a769edf157db42288cebcfb46bda8d53ae47e

Pith citing papers

No inbound Pith citation observations are available.