A Combined Feature Embedding Tools for Multi-Class Software Defect and Identification | Paper Citation Record

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

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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

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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

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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

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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

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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

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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

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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

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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

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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

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Source-reported events for the cited work

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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 2026-08-12T06:34:41.77262+00:00.

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

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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

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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

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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

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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

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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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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

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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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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