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Paper Citation Record · LEDGER

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models

As of 13 August 2026, this Paper Citation Record lists 86 of 86 outbound references and 2 inbound Pith citation observations for arXiv:2411.11389.

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

pith.paper-citation-record.v1
2411.11389 v2

Coverage vector

measured 86 of 86 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:39:41.471542Z

measured 88 of 88 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:43:16.760644Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T21:01:51.399296Z

Reference resolution

86 of 86 outbound references displayed

  • verified exact2
  • verified fuzzy54
  • unresolved29
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 52eebfe3-609c-4c74-b422-9fa2d6063a36 · outbound

This paper cites Fighting against phishing attacks: state of the art and future challenges,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Fighting against phishing attacks: state of the art and future challenges,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.026769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.026769Z digest=sha256:f95044c10f224383f50bd05cb817d8a813aea42442c5216772d21f4e67405bc5

Observation dc61b9cc-ef0a-4db4-a8b9-983fadd7dd60 · outbound

This paper cites Apwg 2024 phishing report,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Apwg 2024 phishing report,

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.032884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.032884Z digest=sha256:53ea98b1528f136a4fd4075251b0d2893033030d9e6b31c670328ab778d04f48

Observation 094b0d39-da07-4b02-be10-8ad344a71100 · outbound

This paper cites A systematic literature review on phishing email detection using natural language processing techniques,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models A systematic literature review on phishing email detection using natural language processing techniques,

Reference 3

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unresolved
no resolver link, observed 2026-08-12T18:39:41.038081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.038081Z digest=sha256:de31fa7c52349e7539b00a512c1f080679800b2973bfa83902f05b53f4bb5c68

Observation 795c7db4-9b49-4ba4-a0af-9dc9a342f6ef · outbound

This paper cites Applying machine learn- ing and natural language processing to detect phishing email,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Applying machine learn- ing and natural language processing to detect phishing email,

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.042928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.042928Z digest=sha256:2e9a7672d7e5a524ab597be3e9964de988c71e0023eae8dcf26a8dccf416a48e

Observation 76bd6ce2-4460-4f49-9fb0-42ef6ed91a85 · outbound

This paper cites ChatSpamDetector: Leveraging Large Language Models for Effective Phishing Email Detection.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models ChatSpamDetector: Leveraging Large Language Models for Effective Phishing Email Detection

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.047995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.047995Z digest=sha256:b5bb20941e5a860a7309bcc086f88c8f4d6da4fc480175eb7f9a0ef51c68dbfc

Observation a2a2129e-2b39-431a-aada-13549a14b1ff · outbound

This paper cites A survey of large language models for cyber threat detection,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models A survey of large language models for cyber threat detection,

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.053192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.053192Z digest=sha256:da3cac7dae8b86e6f7a9bd5a732ccf2a3bfa74dff25c54a815303e2fa3bb3a0b

Observation 4db3bd31-35db-4b6a-9012-678d8486b5cb · outbound

This paper cites Towards security threats of deep learning systems: A survey,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Towards security threats of deep learning systems: A survey,

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.058674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.058674Z digest=sha256:4d57d2c2ecc2c3abb63b1fc1f036a154197ff7be9b5b475df2e1cc405bde1485

Observation e45d0373-11fb-4941-b203-e8bf8a0299eb · outbound

This paper cites Privacy engineering in the wild: Understanding the practitioners’ mindset, organizational aspects, and current practices,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Privacy engineering in the wild: Understanding the practitioners’ mindset, organizational aspects, and current practices,

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.064653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.064653Z digest=sha256:d05fa36de150a1b5d428ca6951153186d3d2c67a723c9e7379b39ada6ca5896d

Observation a2857ce2-7dc5-493a-bc18-dbcd2d562449 · outbound

This paper cites Sok: a comprehensive reexamination of phishing research from the security perspective,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Sok: a comprehensive reexamination of phishing research from the security perspective,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.821703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.069004Z digest=sha256:794f6165bfe489f3892443d3631bdcb8d2b29d70ec13992bb302496688462996

Observation 8d43f7ec-2517-4d07-b131-4faf3e9822bf · outbound

This paper cites Phish- ing email detection using natural language processing techniques: a literature survey,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Phish- ing email detection using natural language processing techniques: a literature survey,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.803764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.074441Z digest=sha256:6cd8940b1173ecf0eb0ce18f8a8069d627782c42d77600044170700ad64ba503

Observation 6b2786e1-129e-4272-b169-5d32a7ad72d5 · outbound

This paper cites Text Data Augmentation: Towards better detection of spear-phishing emails.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Text Data Augmentation: Towards better detection of spear-phishing emails

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-12T18:39:41.731627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.079703Z digest=sha256:126bf360f12fbfdead5f5abb48f4c19a377f3a4155dba37deaa02ae75934f283

Observation 4532749d-1862-4a17-91a5-87f06b3adf5b · outbound

This paper cites Ad- versarial sampling attacks against phishing detection,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Ad- versarial sampling attacks against phishing detection,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.787659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.086006Z digest=sha256:f472b84009ebf7aba926d97c941d9ab8da8e1b7cbae488598ce0151170b19044

Observation 08deb28f-f7eb-4f8b-a391-e50e17bdc346 · outbound

This paper cites Enhancing detection of arabic social spam using data augmentation and machine learning,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Enhancing detection of arabic social spam using data augmentation and machine learning,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.771723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.091644Z digest=sha256:fee51d272822c9a402f7d7e15f14f5264c57a1386bae51aeaf647d86d26e99cd

Observation 51c34854-171b-4835-b823-65d4984b24cb · outbound

This paper cites Data augmenta- tion methods for enhancing robustness in text classifica- tion tasks,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Data augmenta- tion methods for enhancing robustness in text classifica- tion tasks,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.754753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.097179Z digest=sha256:cd034c0d76f979186c19204be3de26f94ceaf29565f7f1091588c14baa396c79

Observation 58ae4c0d-50c6-4424-93a8-d733fcd8c317 · outbound

This paper cites Adversarial examples generation method for chinese text classification,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Adversarial examples generation method for chinese text classification,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.739144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.102691Z digest=sha256:5477534f79eaee999bed6a65f598ff74ef8e0b3dd53311599c16b86572031ff2

Observation 994e753e-8a57-405f-a28c-7f4d72b7cac0 · outbound

This paper cites Rule-based adversarial sample generation for text classification,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Rule-based adversarial sample generation for text classification,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.721809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.107184Z digest=sha256:4f2749da162aa73c562695d2572046489dc2ef614ea14b90809fb84d78252ab5

Observation 3c9e0dab-8486-4e1e-86cd-1b7ec442b2de · outbound

This paper cites An empirical survey of data augmentation for limited data learning in nlp,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models An empirical survey of data augmentation for limited data learning in nlp,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.705758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.112149Z digest=sha256:16d5b6d13fdb37cf15f85ebc6f68ffccbb064169d7fdde7ef8ff81f27d128023

Observation 4fc64b81-a4b4-4c6e-992d-0518752df25b · outbound

This paper cites Adversarial robustness of phishing email detection models,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Adversarial robustness of phishing email detection models,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.689783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.116707Z digest=sha256:c0e8675b4595ff5b8eb3dd41b551d46e68e843f631027efe64f773c66d12c3b3

Observation 8bc3622b-6998-4367-a3fe-30691ec5d7c2 · outbound

This paper cites Data augmentation in classification and segmentation: A survey and new strategies,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Data augmentation in classification and segmentation: A survey and new strategies,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.672922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.122326Z digest=sha256:403b07376b7d9dade7d7c07e1b39ed5758c87d4963f11a62f9d599ce8724c0f9

Observation 12be2dc7-9fc1-4369-b474-3602008268e5 · outbound

This paper cites Analysis and prevention of ai-based phishing email attacks,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Analysis and prevention of ai-based phishing email attacks,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.656311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.126944Z digest=sha256:389d1e126b08eca956ef9e66cd47b5314c6282f4591317e3aa40799f6f473ccb

Observation 81b90e9d-778d-4742-bf91-c86c6facde1a · outbound

This paper cites Phishing or not phishing? a survey on the detection of phishing websites,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Phishing or not phishing? a survey on the detection of phishing websites,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.637612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.132217Z digest=sha256:5534e85420b7a9e51367f94e1c963b2d3debc504b4b3b8f3b240c425785678d8

Observation 806280cb-86dd-4b30-bca0-a3ebccd5b5a8 · outbound

This paper cites Devising and Detecting Phishing: Large Language Models vs. Smaller Human Models.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Devising and Detecting Phishing: Large Language Models vs. Smaller Human Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.136708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.136708Z digest=sha256:059afd3392da69ae0169da37f63c1e83a317bd4ff176935f438a3372fa87be9b

Observation c3ca37bd-1410-4c7a-9780-79451661701b · outbound

This paper cites Lateral Phishing With Large Language Models: A Large Organization Comparative Study.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Lateral Phishing With Large Language Models: A Large Organization Comparative Study

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.141716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.141716Z digest=sha256:5cc5bcf10a3e3b5161b77cf502f3979881063fdd145b65a8a51e3b2e8d3fda8c

Observation e50ce6e2-821a-46c2-9c0b-490dd6602de2 · outbound

This paper cites A survey on explainable anomaly detection,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models A survey on explainable anomaly detection,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.617910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.147233Z digest=sha256:6a89bbd92c0add17c7cf2eecbc7b6627335d4bbbd01ad64cb674e639003001d1

Observation 5da470cf-63f7-485e-a4b4-27472e435a90 · outbound

This paper cites Detection of ai-generated emails-a case study,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Detection of ai-generated emails-a case study,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.601276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.151841Z digest=sha256:565c8882c451a56435cdc6c44ed8f38e4e4efd5b4336cedeb586dfdcbd950ed4

Observation 3c0db142-7359-4b59-ab9c-62410411b312 · outbound

This paper cites Phishing and social engineering attack prevention with llms,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Phishing and social engineering attack prevention with llms,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.584159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.156794Z digest=sha256:e999d578a54e494afe70cf57039c41b7fbb81916b4fc3303e3ec6c4c731a049f

Observation 90978786-70bd-45ed-ab3f-4bd66c45074a · outbound

This paper cites an unresolved cited work.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-12T18:39:42.567446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.162054Z digest=sha256:cbf7b6c8811565f67682d4216d86f6ac23a4cb695c42b4c132c5fe9242d268d7

Observation eae32383-399a-4372-93f2-6dee1da1265d · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Gemini: A Family of Highly Capable Multimodal Models

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.166967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.166967Z digest=sha256:29fe22efdf94dad2e15b6ec7e3a2647cdcf969531ac9fc091a53cf519be61b22

Observation 86c9c4b2-1b95-4993-bf66-c7394fb5a341 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models LoRA: Low-Rank Adaptation of Large Language Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.172683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.172683Z digest=sha256:37758d1418d8e9ee7b30611c21e72f6da9dd7f3b9cd8af367b427bca271b28cb

Observation fcbbffe8-77ed-4547-ba2c-96c853d80c2d · outbound

This paper cites Bi-lstm model to increase accuracy in text classification: Combining word2vec cnn and attention mechanism,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Bi-lstm model to increase accuracy in text classification: Combining word2vec cnn and attention mechanism,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.550393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.177820Z digest=sha256:d5536184c830ebbcba737b4212e3ef5ff395b86f13a2f48c34dd39bd3224ee7e

Observation 80a51a50-155a-4745-b468-ae2c27c94391 · outbound

This paper cites An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.182556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.182556Z digest=sha256:f4298597cc24dee6a1f1bdedb13064fac3a9c6b9f9b708a985f6e7544fce7133

Observation 4a683be3-42d8-44a4-837f-40c904c3fb68 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Chain-of-thought prompting elicits reasoning in large language models,

Reference 32

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unresolved
no resolver link, observed 2026-08-12T18:39:41.187427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.187427Z digest=sha256:3923eb076654d7ec15a8853e1f517f73606f971a41f56fea6ab579149201a44b

Observation 038dcbc6-dfec-490d-8903-2cb65b719335 · outbound

This paper cites Isolation forest,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Isolation forest,

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.192687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.192687Z digest=sha256:270a4eb74255dded8b4b283327165656bd5b1689a1c5d3853a015fdcaec240aa

Observation b2fa371b-9454-44a9-b8f3-6fe75349721f · outbound

This paper cites Latent dirichlet allocation,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Latent dirichlet allocation,

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.197680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.197680Z digest=sha256:5bdfd71e7a43f8ab985a286ee938092455b1573a660ef3c97e232b52c6c8b642

Observation d4a16c91-b51f-4702-a5bd-db28849b363b · outbound

This paper cites The science of persuasion,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models The science of persuasion,

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.203815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.203815Z digest=sha256:dd5b9d0aeae702f39d5eed1f69f170e9bc847f4319a84f69cd511f08bb591a22

Observation 8a56f8d8-e903-49f8-98e3-9efcf90b5833 · outbound

This paper cites Concept induction: Analyzing unstructured text with high-level concepts using lloom,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Concept induction: Analyzing unstructured text with high-level concepts using lloom,

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.486197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.209116Z digest=sha256:9c686340d07f7e006dbeda38d088f413c484271c7d36658ee22af5bcd6c675ad

Observation 20741667-1779-4d82-b6e7-1887605950b3 · outbound

This paper cites The development and psychometric properties of liwc-22,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models The development and psychometric properties of liwc-22,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.467962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.215267Z digest=sha256:a8152de70181ba8070d349980ddf429614829d61d091398d92f5acb815190e4b

Observation 6594b9b5-999f-4226-90b7-e7147e8acefc · outbound

This paper cites Optimizing semantic coherence in topic models,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Optimizing semantic coherence in topic models,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.451354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.220639Z digest=sha256:c89a996133ae1c7d57b7df369d64ccbd732676a541cd99c265f158e3e4889532

Observation 1a9ea117-a2bc-4f22-ae75-8c9356fe60f4 · outbound

This paper cites Class-based n-gram models of natural language,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Class-based n-gram models of natural language,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.226525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.226525Z digest=sha256:14e0bceb4c99a5c8d180e137c321407f585789515b5dc7fa4e53d946fd70bcca

Observation f423a8c3-58a6-46f7-ab5d-0f7694b48861 · outbound

This paper cites Interpreting tf-idf term weights as making relevance decisions,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Interpreting tf-idf term weights as making relevance decisions,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.423305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.231793Z digest=sha256:3c0bf894ba159adad2a75ec87434d7daf3b0a9c46d9a767fb169bf4e9744925d

Observation 9b133c9a-c425-44a3-beca-b01e00ed3d90 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Explaining and Harnessing Adversarial Examples

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.236781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.236781Z digest=sha256:16b798a52196058b3204869419e461348133e5c9e8cf1257415b792a734be2e8

Observation 21dc6380-18e5-41b4-bdf5-f7100ca25a96 · outbound

This paper cites Machine literature searching viii. operational criteria for designing information retrieval systems,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Machine literature searching viii. operational criteria for designing information retrieval systems,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.407547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.242214Z digest=sha256:a30bf09de7747d75bbe905173818642366a6eba4a9caa7bcb29420492d5feb07

Observation 7d9e5658-1dc4-4084-bcfc-880bd47a00fa · outbound

This paper cites Iwspa phishing dataset,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Iwspa phishing dataset,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.391085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.247908Z digest=sha256:409125db958ee64d40de8817eb5469302657a7d25f6922ec38d83003d0556ec1

Observation 1aad8c3b-6ba3-48d2-aae5-1b90177859ff · outbound

This paper cites Nazario phishing dataset,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Nazario phishing dataset,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.373022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.252703Z digest=sha256:dfe974b014ea4fdc99043a09f22c0c01f555bf73f6b6eafe2c7ed85d8bf4c7ec

Observation 010805cb-29b1-435f-8468-c0068298df8f · outbound

This paper cites Miller smiles phishing dataset,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Miller smiles phishing dataset,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.355948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.257430Z digest=sha256:b0edc4a47be7358071b8f31d15481accde306a078f66fcabd8133abd2e813003

Observation f7b7a90b-4904-4582-b955-56350f24548e · outbound

This paper cites Phish bowl phishing dataset,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Phish bowl phishing dataset,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.337586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.262079Z digest=sha256:27c92a48e22bb2b3d60a3fcc8bd08645241cbacf41c5e13696a3ec0175aa5642

Observation 13b9ddc8-ea17-4f7a-9cf5-3fbb64c0c920 · outbound

This paper cites Nigerian fraud dataset,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Nigerian fraud dataset,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.320493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.267539Z digest=sha256:2dad2ffa74d21e04acd68f8e78dbd04858475bf47d62d98fd505205fca7aeacb

Observation e1836623-8c72-4a2a-abc7-c8fb779500c0 · outbound

This paper cites An improved transformer-based model for detecting phishing, spam and ham emails: A large language model approach,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models An improved transformer-based model for detecting phishing, spam and ham emails: A large language model approach,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.302181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.272172Z digest=sha256:3671b13f44c2d3ec6c00dc058262ffbb66c12e13dfb97775b1ce9e138bd56f4f

Observation 7144e5d8-9ce1-4c11-ac9a-185ae0f97100 · outbound

This paper cites The psychological meaning of words: Liwc and computerized text analysis methods,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models The psychological meaning of words: Liwc and computerized text analysis methods,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.284201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.277068Z digest=sha256:2aa3c07b0d65b63d5f90931a0aad9e24c1f2a362db66975ea3c77dd64f5ace3d

Observation 1b6f42fe-f64d-44d0-bc52-6a7c56c1e160 · outbound

This paper cites Changing others’ beliefs online: Online comments’ persuasiveness,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Changing others’ beliefs online: Online comments’ persuasiveness,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.265494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.281790Z digest=sha256:e33685fa55df4bde8f1bc9992a4f4cf9baf62fe12ed196447c72eaa7f9a80b3e

Observation 29549bb9-ebcc-4efc-aaad-bcf074a75523 · outbound

This paper cites Cognitive triaging of phishing attacks,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Cognitive triaging of phishing attacks,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.248062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.287223Z digest=sha256:7e7c24ec6f626803cee1ad02f22160f5afcc89d1e3dfe5d0093d275db5f3f07f

Observation 098a2e7b-b673-4821-beef-98e6c52dfa41 · outbound

This paper cites The development and psychometric properties of liwc2015,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models The development and psychometric properties of liwc2015,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.231202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.291935Z digest=sha256:b3a8872d4e76f59dee05334876c8bd7b6fd458b98b8a33e2dcb112edad83333d

Observation f8eb5c3d-3cb5-488b-aa7f-4c70ee035436 · outbound

This paper cites InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.296911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.296911Z digest=sha256:f873fac348da080711693ea7f4a38a9f98764ef071beccf649dad0dd1f9ef1ab

Observation 20668650-a631-44d9-b9fa-9a8db1d143e8 · outbound

This paper cites Generating nat- ural language adversarial examples through probability weighted word saliency,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Generating nat- ural language adversarial examples through probability weighted word saliency,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.214504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.301787Z digest=sha256:22095e7eb6dc0a5adde7e4a03d096b58397671a4a903858f58b9f2eb63b2f42d

Observation f4bf9bb6-2251-4f7f-8c11-71b92cf0e99a · outbound

This paper cites Combating Adversarial Misspellings with Robust Word Recognition.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Combating Adversarial Misspellings with Robust Word Recognition

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.306847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.306847Z digest=sha256:14402bcc057a18d76187f08582bbab0643ddd15f5c24e565a17138a52e7d0505

Observation 86f85598-28a7-4237-b0df-d041620a112a · outbound

This paper cites Black-box generation of adversarial text sequences to evade deep learning classifiers,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Black-box generation of adversarial text sequences to evade deep learning classifiers,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.197184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.311808Z digest=sha256:e6d868090a7a74a0e990efabdbb6cd16fc10623a13bfb9e37cba21f233112c34

Observation 1dbde074-7a50-4f6b-99ae-7efa81fc7f48 · outbound

This paper cites Chatgpt and a new academic reality: Arti- ficial intelligence-written research papers and the ethics of the large language models in scholarly publishing,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Chatgpt and a new academic reality: Arti- ficial intelligence-written research papers and the ethics of the large language models in scholarly publishing,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.179947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.316618Z digest=sha256:52397d24754c93d924bbebf1164a411ed1d33c5ac0dd8f7b64e91546b9f3d4cc

Observation 8c680be2-342f-403a-a74b-4a740335df54 · outbound

This paper cites Social engineering in cybersecurity: Effect mechanisms, human vulnerabilities and attack methods,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Social engineering in cybersecurity: Effect mechanisms, human vulnerabilities and attack methods,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.163516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.321781Z digest=sha256:f4e6666b90b82c479029e272858b5a5dacff78d47d1f9692171af1046a375913

Observation 4e498037-3c7e-48a9-917d-485cfcf4edb8 · outbound

This paper cites Udh: Universal deep hiding for steganography, water- marking, and light field messaging,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Udh: Universal deep hiding for steganography, water- marking, and light field messaging,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.146765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.327432Z digest=sha256:05d4c83af1cc27f8007b3df6329709af341f39af71d2aa9289ea2d704920828e

Observation 953bcc34-2c45-4aae-8861-a482e637827c · outbound

This paper cites Towards adversarial phishing detection,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Towards adversarial phishing detection,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.130034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.332436Z digest=sha256:2c574d2dd00c2c1299876d04c2b15f678d6f7b663064e2fcd3bcd0e7abe2ece9

Observation cb435f40-9737-4873-a9d9-a353caa279bf · outbound

This paper cites Hooked: A Real-World Study on QR Code Phishing.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Hooked: A Real-World Study on QR Code Phishing

Reference 61

Resolution
verified exact
local_arxiv, observed 2026-08-12T18:39:41.570766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.337679Z digest=sha256:5e2238a372dae1c04f9857f5e47e6c5b5fb9bf95ce9813bb9dfe404fbe77fbfc

Observation 4a1c88b9-2786-4faa-9229-c014a8dbfae7 · outbound

This paper cites An image is worth a thousand toxic words: A metamorphic testing framework for content moderation software,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models An image is worth a thousand toxic words: A metamorphic testing framework for content moderation software,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.113311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.343302Z digest=sha256:8421a1c9ef0605bed8c6f6058bc457e4d1cacdc4466409ef28a31073abdadc1b

Observation a5d29b2f-5e2b-431c-87e2-442db2712b54 · outbound

This paper cites {KnowPhish}: Large lan- guage models meet multimodal knowledge graphs for enhancing {Reference-Based} phishing detection,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models {KnowPhish}: Large lan- guage models meet multimodal knowledge graphs for enhancing {Reference-Based} phishing detection,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.095491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.348426Z digest=sha256:d573dc38ff8447f7d0392a6b2191da1a6340481eb638309dcb8a4f8dd8cd2028

Observation f130d1d3-16cc-4651-ac58-609dfbab8fd9 · outbound

This paper cites From chatbots to phishbots?: Phishing scam generation in commercial large language models,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models From chatbots to phishbots?: Phishing scam generation in commercial large language models,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.077017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.353430Z digest=sha256:823ebf80909952ef0d5f97810aa6c1a71603e9c9a4f3f474f77bdf41290f0e5b

Observation ff071e10-7593-484b-a28b-60f79d68adae · outbound

This paper cites Chatgpt’s security risks and benefits: of- fensive and defensive use-cases, mitigation measures, and future implications,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Chatgpt’s security risks and benefits: of- fensive and defensive use-cases, mitigation measures, and future implications,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.057344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.358762Z digest=sha256:7a0a901579e0ac0fdea0a74ec46f463d58cd0b7f3195dfdaec1558db41778721

Observation d21a6dae-35de-42ab-a19f-5b801ba2af03 · outbound

This paper cites A survey on dataset quality in machine learning,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models A survey on dataset quality in machine learning,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.038508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.364941Z digest=sha256:5cb774c4d02808e71131857dd3733a343468b98ea31b5b74c01b2fec423c94b3

Observation 8e6a8c87-880e-44e8-8279-27b1c42e91ae · outbound

This paper cites Generating optimal attack paths in generative adversarial phishing,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Generating optimal attack paths in generative adversarial phishing,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.020780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.370287Z digest=sha256:b26fc72e66a21ae7ac0ac5b5aa96cb1cfd6d1986d3030428dabaa9b6c4e4f547

Observation ca6f4505-373e-46a4-b538-1f22275790c0 · outbound

This paper cites Weaponizing data science for social engineering: Automated e2e spear phishing on twitter,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Weaponizing data science for social engineering: Automated e2e spear phishing on twitter,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:42.002936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.375410Z digest=sha256:5a6b31704ca612ad398654e27fbfe1d7a5d45cca9ba45e3428747756051fbe95

Observation e5e2031d-3ca6-420c-be97-b984434d745f · outbound

This paper cites Is bert really robust? a strong baseline for natural language attack on text classification and entailment,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Is bert really robust? a strong baseline for natural language attack on text classification and entailment,

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.380768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.380768Z digest=sha256:405d611ff3387b988801d42561ccc84e551c0b40d298d62b86dbfa2c5ba58b06

Observation 1f4f1b29-d783-4968-a3bd-5f9b869bbe0e · outbound

This paper cites Social engineering in cybersecurity: The evolution of a concept,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Social engineering in cybersecurity: The evolution of a concept,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:41.975456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.386811Z digest=sha256:d0afb8107cf3d224b012fc01c4cf7bc353feacdfc566c054c864e04be87704f6

Observation aa3bcd12-4813-43b3-afe5-c31cb5cd805c · outbound

This paper cites Defining social engineer- ing in cybersecurity,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Defining social engineer- ing in cybersecurity,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:41.959531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.392894Z digest=sha256:ee3bd3e03122b371b17526c48d710795f483902d6817ba23a522a86d684c4368

Observation 2216b263-2f0c-47cd-8657-06460f1457d0 · outbound

This paper cites Email summarization to assist users in phishing iden- tification,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Email summarization to assist users in phishing iden- tification,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:41.942058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.398641Z digest=sha256:e3ff4eabef7119cf983d3e573471425bddd7c8c3a6afec8c27e406bb0af0e99f

Observation e5f25af4-262e-4669-95fa-3f6b8a1cc229 · outbound

This paper cites Email phishing and signal detection: How persuasion principles and personality influence response patterns and accuracy,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Email phishing and signal detection: How persuasion principles and personality influence response patterns and accuracy,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:41.922358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.403593Z digest=sha256:8bb58570ef30f7705b5dba7ea495a0f664322c9a2dd5c93ab7f1a633f14d571d

Observation 4a6da0a2-010d-4217-9c01-ca7f0fb10e2d · outbound

This paper cites Detection method of phish- ing email based on persuasion principle,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Detection method of phish- ing email based on persuasion principle,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:41.905775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.408576Z digest=sha256:d26b6de90f645391210a2c974b4a04f1fb9c65e3d373b5fdf510c302fc6a1853

Observation 2eec8388-374a-486a-8ef1-621b4f4666e6 · outbound

This paper cites Utilizing large language models with human feedback integration for generating dedicated warning for phishing emails,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Utilizing large language models with human feedback integration for generating dedicated warning for phishing emails,

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:41.889090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.413804Z digest=sha256:5f65ea2c357082b805d1aa42a3c02599e01a8376100f1da48627cfe6106c109e

Observation 5245d107-19be-4100-95f3-099899bfdf88 · outbound

This paper cites Digital Deception: Generative Artificial Intelligence in Social Engineering and Phishing.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Digital Deception: Generative Artificial Intelligence in Social Engineering and Phishing

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.419279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.419279Z digest=sha256:2073a5b7bca6ab341a735c7444bcd4de170548af8484435319f798b27355e09a

Observation 0a1a05e6-5607-4f49-973d-b8445b6a248d · outbound

This paper cites Social engineering at- tacks: A survey,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Social engineering at- tacks: A survey,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:41.872099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.425317Z digest=sha256:afe514cf648085992f9c846f59e5db9baab8979188e75e63b4878cfac0bb7a6e

Observation 74a0f2c4-e3cf-4a1b-8a91-ad495a96bcbc · outbound

This paper cites Ai2tale: An innovative information theory-based approach for learning to localize phishing attacks,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Ai2tale: An innovative information theory-based approach for learning to localize phishing attacks,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:41.855218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.430238Z digest=sha256:00271756b94fe1d6256449f3d4a5c254512d1a9ef7d4025804743f7f548ceb26

Observation 03dee996-bbb4-4ca1-af87-3273fbd90921 · outbound

This paper cites Generative adversarial nets,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Generative adversarial nets,

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.435087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.435087Z digest=sha256:8a594fb2ead75e9e75cd4c73a1a94fb753bb2d40233949d3d57cb904ae6d303d

Observation a78484e5-beec-42f1-9e1a-74dbd407442d · outbound

This paper cites Conditional Generative Adversarial Nets.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Conditional Generative Adversarial Nets

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.440306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.440306Z digest=sha256:d1d4a726a95c939a06e43f74ea3e79a77186210439fe8cad9a39140cbabad6df

Observation e8054ac3-3206-4fa8-b86b-8599eaeef13f · outbound

This paper cites an unresolved cited work.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Unresolved cited work

Reference 81

Resolution
unresolved
raw_fallback, observed 2026-08-12T18:39:41.827141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.445790Z digest=sha256:c6b32bb2d996057a0ba9904ae329928752b9941024840d578b660a87410e1799

Observation c98282c8-1aab-44c1-9715-e45de82ee1a7 · outbound

This paper cites Evaluating ChatGPT's Performance for Multilingual and Emoji-based Hate Speech Detection.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Evaluating ChatGPT's Performance for Multilingual and Emoji-based Hate Speech Detection

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.450816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.450816Z digest=sha256:35cb64bc12d842df7cfd2b5ce60566f6f3a566d41854a3d8fa1ef7aac46c0e4c

Observation 429f8a9e-6e80-4d63-88bb-9f217533fadf · outbound

This paper cites Is chatgpt better than human annotators? potential and limitations of chatgpt in explaining implicit hate speech,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Is chatgpt better than human annotators? potential and limitations of chatgpt in explaining implicit hate speech,

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:41.810918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.456183Z digest=sha256:771cf0372398d7639c54ea0a8ccf44d5b92fe8cc225a2b57eec2ab885962bd21

Observation bcb0d1f9-8ed2-41de-bd17-5c6149c80de8 · outbound

This paper cites Cross-validation methods,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Cross-validation methods,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:39:41.792595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.461231Z digest=sha256:e1e590b2d4c2d22d44b6bd55e9a0fd44f0955e912dcb7d79730a8a7cc43eea24

Observation 29c487e1-ef66-4e23-a5ab-1d268dd5d915 · outbound

This paper cites Language models are unsupervised multitask learners,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Language models are unsupervised multitask learners,

Reference 85

Resolution
unresolved
no resolver link, observed 2026-08-12T18:39:41.466730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:39:41.466730Z digest=sha256:77a354ac65e7b60d74cf96b1edd869e3691aeb1149de52b5a36f854df34bd3be

Observation 33a439d9-b607-413c-bf89-039db150184a · outbound

This paper cites Nigerian.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Nigerian

Reference 86

Resolution
malformed identifier
raw_fallback, observed 2026-08-12T18:39:41.764849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:39:41.471542Z digest=sha256:cf3ec1fd7d9a697aa7954b5b0262ca01d76dfa33fa84bd5003545f41a00a871e

Pith citing papers

Observation ed0d4329-1abe-4c0e-82e6-d0fb88faac3e · inbound

Can We End the Cat-and-Mouse Game? Simulating Self-Evolving Phishing Attacks with LLMs and Genetic Algorithms cites this paper.

Can We End the Cat-and-Mouse Game? Simulating Self-Evolving Phishing Attacks with LLMs and Genetic Algorithms PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T12:43:16.760644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:43:16.760644Z digest=sha256:0a7c4905ba0edd1754be2d628d0a860543d856cc9dbf9b801571557bfdc7d4a9

Observation 0628af0d-6c0d-498e-8f65-746c7af05a5e · inbound

SoK: Exposing the Generation and Detection Gaps in LLM-Generated Phishing cites this paper.

SoK: Exposing the Generation and Detection Gaps in LLM-Generated Phishing PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-18T21:01:51.402303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-18T20:57:03.172931Z digest=sha256:dd6331b6b299dc67784ada2d198857d07a3487aba4b6ba061201646fe397c7c6