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Paper Citation Record · LEDGER

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models

As of 22 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 5 inbound Pith citation observations for arXiv:2412.00166.

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

pith.paper-citation-record.v1
2412.00166 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:54:33.843438Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:03:44.352631Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:39:36.878631Z

Reference resolution

35 of 35 outbound references displayed

  • verified exact2
  • verified fuzzy16
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3bd9337a-61a6-4014-b559-9d43eff35bac · outbound

This paper cites In: Proceedings of the anti-phishing working groups 2nd annual eCrime researchers summit.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models In: Proceedings of the anti-phishing working groups 2nd annual eCrime researchers summit

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-12T05:54:34.358373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.712810Z digest=sha256:b86d9c553c8b415f33f4ca48452e01fcc24c7dc9d9ef30d230424786c0cbb7cd

Observation e5665290-d908-40ee-8f38-e2d59826bca8 · outbound

This paper cites GPT-4 Technical Report.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models GPT-4 Technical Report

Reference 2

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no resolver link, observed 2026-08-12T05:54:33.717192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.717192Z digest=sha256:1d9270a8f1261dd47cdb293934009c96ace663510cc064c71f49f29e133a9ff2

Observation 552e6cf2-c4d1-43e9-8994-a2a33a384b7e · outbound

This paper cites Advances in Engineering Software 173, 103288 (Nov 2022).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Advances in Engineering Software 173, 103288 (Nov 2022)

Reference 3

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no resolver link, observed 2026-08-12T05:54:33.721515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.721515Z digest=sha256:7715e3773ea4818b84f5a1d50e2b71e15f61e9a164f561f82422d020edd61784

Observation 9e8c075b-5c51-4609-8f54-4fea9e387030 · outbound

This paper cites PaLM 2 Technical Report.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models PaLM 2 Technical Report

Reference 4

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no resolver link, observed 2026-08-12T05:54:33.725982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.725982Z digest=sha256:5a05e0c3d26a0908590d5f97f95eb67b17b2fd9db2cec32bcb9c57df217e4248

Observation 2835eb15-3c4e-4639-af4f-da2ff397cca7 · outbound

This paper cites Advances in neural information processing systems 33, 1877–1901 (2020).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Advances in neural information processing systems 33, 1877–1901 (2020)

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.730103Z digest=sha256:5735fb66e02fd1aa421ec5fb846401a00effb57cdd38436e31465069d32212dc

Observation bf42fdd4-64f7-4cac-86a1-697566abe85e · outbound

This paper cites ACM Transactions on Intelligent Systems and Technology (2023).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models ACM Transactions on Intelligent Systems and Technology (2023)

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-12T05:54:34.340641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.733728Z digest=sha256:42f1204a42bb10764a786e40120a8b70d9e552db0a1907fbba0014449348f34d

Observation c9537c7a-20a5-4ad9-9dff-178e71a610ea · outbound

This paper cites In: International work- shop on multiple classifier systems.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models In: International work- shop on multiple classifier systems

Reference 7

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no resolver link, observed 2026-08-12T05:54:33.737874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.737874Z digest=sha256:355ef9dc206790418350c6c6763704fdab138048e69c273adf0446d7335c8468

Observation fe271030-bd91-4ac3-93be-e73ea712f1d2 · outbound

This paper cites Nature Machine Intelligence 5(3), 220–235 (2023).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Nature Machine Intelligence 5(3), 220–235 (2023)

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.741441Z digest=sha256:b6c2a27827e54d7f6ba77089b8581a39bc61e4ed292c6e97a84dfe4dbe762d69

Observation c31bd3c2-be97-4060-8b28-beb3c376f841 · outbound

This paper cites Comparing BERT against traditional machine learning text classification.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Comparing BERT against traditional machine learning text classification

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.744951Z digest=sha256:1ed9197c3c36149b0e6e2f64a14cf2154daab104eb607bd3e3822113ef753901

Observation 5b35ae4a-2e3c-4355-bf8d-b0ad4680133b · outbound

This paper cites In: 2013 international conference on control communication and computing (ICCC).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models In: 2013 international conference on control communication and computing (ICCC)

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-12T05:54:34.311358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.748810Z digest=sha256:94730f1284785ca37d67f792f9539169de28bdb0b011f96384400809246c5dbb

Observation 8e787b75-84ac-41f7-8dc2-9ab93015309a · outbound

This paper cites In: CHI Conference on Human Factors in Computing Systems Extended Abstracts.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models In: CHI Conference on Human Factors in Computing Systems Extended Abstracts

Reference 11

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raw_fallback, observed 2026-08-12T05:54:34.301005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.752349Z digest=sha256:0ac4d6d0a32b12138fbab1955c14defe4aeefaa140225f461c70b4f0f3691002

Observation fb65b010-92d2-45c3-86e1-55094c18e8c1 · outbound

This paper cites In: Security and Privacy in Communication Networks: 13th International Conference, SecureComm 2017, Niagara Falls, ON, Canada, October 22–25, 2017, Proceedings 13.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models In: Security and Privacy in Communication Networks: 13th International Conference, SecureComm 2017, Niagara Falls, ON, Canada, October 22–25, 2017, Proceedings 13

Reference 12

Resolution
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raw_fallback, observed 2026-08-12T05:54:34.289995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.756184Z digest=sha256:dc89302280fb79fdb16365d21dc15f4700fd086e94b4f61da62416764afda0b2

Observation 2bfe76a6-adeb-46b6-8760-cd4dae116b32 · outbound

This paper cites Challenges and Applications of Large Language Models.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Challenges and Applications of Large Language Models

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.759836Z digest=sha256:92e1682b2ac27dae77a3e1341cba4c60594728544ddbab1d64ea47990f434de2

Observation b0944316-a823-4485-9e0a-5b848536179e · outbound

This paper cites Pattern Analysis & Applications 6, 22–31 (2003) 14 F.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Pattern Analysis & Applications 6, 22–31 (2003) 14 F

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-12T05:54:34.278116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.763903Z digest=sha256:411e5df85f24fb7fec82b21f061395d8a71a51f01f705770297e8c1a35d93541

Observation 0886787b-a93a-4f64-a780-87a26f911505 · outbound

This paper cites URLNet: Learning a URL Representation with Deep Learning for Malicious URL Detection.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models URLNet: Learning a URL Representation with Deep Learning for Malicious URL Detection

Reference 15

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no resolver link, observed 2026-08-12T05:54:33.767998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.767998Z digest=sha256:68b83c494de7b9c7069c07aeea07431945ac0411a65484fe3edc4561f92f8718

Observation ce6d6764-bb67-4378-a9a3-b84c34003bf4 · outbound

This paper cites International Journal of Computer Applications 181(23), 45– 47 (Oct 2018).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models International Journal of Computer Applications 181(23), 45– 47 (Oct 2018)

Reference 16

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verified exact
doi, observed 2026-08-12T05:54:33.898904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.772262Z digest=sha256:fc0de1d63ec0c2d5c7c3835d25dee1feee5bbf2e3ad8b89caf9afbe322b35f19

Observation af0b652b-daee-45c4-a08b-cb05305fd9a4 · outbound

This paper cites IEEE Transactions on Network and Service Management 11(4), 458–471 (2014).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models IEEE Transactions on Network and Service Management 11(4), 458–471 (2014)

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-12T05:54:34.266797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.776032Z digest=sha256:ab5ab600a915832391848b790c0b870c6db7c93c02ad70693f1ee501a29cecbb

Observation fb8ad9e4-54d7-4346-9d67-34c4071d6c69 · outbound

This paper cites In: International Conference on Data Intelligence and Cognitive Informatics.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models In: International Conference on Data Intelligence and Cognitive Informatics

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:54:34.255354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.779487Z digest=sha256:d22bc356298b3ed7ab2f54587a24c2a559b7e5974882c0eb8a9f34b512fece30

Observation ca60839f-6907-4780-a6e1-fb973677c47f · outbound

This paper cites In: Proceedings of the ACL 2010 conference short papers.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models In: Proceedings of the ACL 2010 conference short papers

Reference 19

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raw_fallback, observed 2026-08-12T05:54:34.244613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.783283Z digest=sha256:8e6fce97f1631b04c14f52e014b86832978dff5e3462a68316beee0df57cdf0c

Observation ea16649b-e079-4cb6-8980-6cad0e12b222 · outbound

This paper cites In: Futuristic Trends in Networks and Computing Technologies: Se- lect Proceedings of Fourth International Conference on FTNCT 2021.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models In: Futuristic Trends in Networks and Computing Technologies: Se- lect Proceedings of Fourth International Conference on FTNCT 2021

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:54:34.233956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.787003Z digest=sha256:660eca28ffc52c1cef71a245be656e6ea68116ac06affca07204850dd803cbbe

Observation c7e13712-1db9-4aa4-8207-6c7cfc737dfb · outbound

This paper cites IEEE Access (2024).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models IEEE Access (2024)

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.790473Z digest=sha256:238a643795efe8969e964ed9d13312ae10a17bb1a7266e5448767933651b41ca

Observation 138e3b64-a22f-4cbd-8327-1279071036bb · outbound

This paper cites Internet of Things and Cyber- Physical Systems (2023).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Internet of Things and Cyber- Physical Systems (2023)

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:54:34.216116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.794013Z digest=sha256:abd33dd0262f393ff867fd8d06d468921c811fee3aaa9686e24b3f01bf61edd4

Observation 0bec4f44-feaa-42e8-ba9d-da05aedbc9b7 · outbound

This paper cites Expert Systems with Applications 117, 345–357 (Mar 2019).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Expert Systems with Applications 117, 345–357 (Mar 2019)

Reference 23

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no resolver link, observed 2026-08-12T05:54:33.797535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.797535Z digest=sha256:e0f1fbf656e7bb4bead23267f96e3d52ebf1e93092930ffc12d9a75e8bf2446f

Observation 3321b2e5-f832-484a-8546-df7b56a05466 · outbound

This paper cites In: 2020 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models In: 2020 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-12T05:54:34.204668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.801017Z digest=sha256:4899ae6b4fdc015f9f447d8c6e026fc9e5406d946442757b046f68efb4e0467b

Observation f07909b7-c7c0-42b5-b9bc-5df74a1dcb77 · outbound

This paper cites an unresolved cited work.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Unresolved cited work

Reference 25

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no resolver link, observed 2026-08-12T05:54:33.804497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.804497Z digest=sha256:a6c9677566db766fda735d1e6860e37181cd774a9ad097a9b9ee992c97f3474e

Observation fe67cf67-d0c7-463e-94db-8e680648442a · outbound

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

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Gemini: A Family of Highly Capable Multimodal Models

Reference 26

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no resolver link, observed 2026-08-12T05:54:33.808001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.808001Z digest=sha256:244ebda06f24a92117ba3b9431ec1acb33184ebc1aa70d5b6e8665cd35773a2b

Observation 5923979d-68b9-4bcb-8ea3-458c1564f5e0 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-12T05:54:33.812178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.812178Z digest=sha256:cfb67d583858fe3b718df1ebfb4f3652ea75ddee62268d6233b2b56ab036c54a

Observation ae79573f-fe21-4444-adb4-2bd8db301d50 · outbound

This paper cites Evaluating the Efficacy of Prompt-Engineered Large Multimodal Models Versus Fine-Tuned Vision Transformers in Image-Based Security Applications.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Evaluating the Efficacy of Prompt-Engineered Large Multimodal Models Versus Fine-Tuned Vision Transformers in Image-Based Security Applications

Reference 28

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unresolved
no resolver link, observed 2026-08-12T05:54:33.816350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.816350Z digest=sha256:879608f197e7b4160ab418aef0651b203b7350250cc549920a7ce2181cadc547

Observation d7fe7f00-5846-4c86-b883-962104e635f0 · outbound

This paper cites Machine Learning and Knowledge Extrac- tion 6(1), 367–384 (2024).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Machine Learning and Knowledge Extrac- tion 6(1), 367–384 (2024)

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:54:34.186562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.820250Z digest=sha256:7d1caae3db15b6f2dd2b9d5613942578a7d760d02b8711e641b108040720debd

Observation e810e55d-d42e-4772-a3da-e5d38aa6aefb · outbound

This paper cites Advances in neural information pro- cessing systems 30 (2017) Assessing Majority Voting Strategies for Phishing Detection with LLMs 15.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Advances in neural information pro- cessing systems 30 (2017) Assessing Majority Voting Strategies for Phishing Detection with LLMs 15

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:54:34.174568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.823874Z digest=sha256:83320887c72ac212d7bd8d805d97d789190bc5110f439f6f12f8e49798e2f427

Observation 860245f4-c9c8-481c-a2f9-cbc39f33a9b0 · outbound

This paper cites Emergent Abilities of Large Language Models.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Emergent Abilities of Large Language Models

Reference 31

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no resolver link, observed 2026-08-12T05:54:33.827643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e858b11d-fb67-4c03-b3a9-f73e705a2d5f · outbound

This paper cites Computer Networks 178, 107275 (Sep 2020).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Computer Networks 178, 107275 (Sep 2020)

Reference 32

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no resolver link, observed 2026-08-12T05:54:33.831671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:54:33.831671Z digest=sha256:d96c674f0f4ee0e3a9db89f4107a00f79183c9a69e3a5d2f7b4c37e81d0fda68

Observation 920b3746-8500-43f5-ac6f-9cc397f5c17b · outbound

This paper cites A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models

Reference 33

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no resolver link, observed 2026-08-12T05:54:33.835634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d3738c40-6828-48ce-8a08-d110c79025c8 · outbound

This paper cites Neurocomputing 557, 126708 (2023).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Neurocomputing 557, 126708 (2023)

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:54:34.163286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.839620Z digest=sha256:73eb2049df4085fe056573ad340c7a9d0432dbd2ae1dd87728d3e13ef2a03505

Observation 8aabce6f-3bf5-4612-bc4e-cf3467e0b20e · outbound

This paper cites Human-centric Computing and Information Sciences 7(1), 17 (Jun 2017).

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Human-centric Computing and Information Sciences 7(1), 17 (Jun 2017)

Reference 35

Resolution
verified exact
doi, observed 2026-08-12T05:54:33.878166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:54:33.843438Z digest=sha256:bab7349ab9446db6b6c272ce5c675e31f206e6a1d6ce3edc70fff9392980ccc9

Pith citing papers

Observation cbc503ac-be35-4202-85ca-a68fe3ccdee3 · inbound

Optimal Query Allocation in Extractive QA with LLMs: A Learning-to-Defer Framework with Theoretical Guarantees cites this paper.

Optimal Query Allocation in Extractive QA with LLMs: A Learning-to-Defer Framework with Theoretical Guarantees To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-23T18:53:21.463541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-23T18:49:39.718108Z digest=sha256:c1de4fea4f19da8c176f84b27f51a5240831cfffe0a1c8919f270a6bb8ab5707

Observation a4a889ec-d377-4670-99b8-29f2bc8ed743 · inbound

Large Multimodal Agents for Accurate Phishing Detection with Enhanced Token Optimization and Cost Reduction cites this paper.

Large Multimodal Agents for Accurate Phishing Detection with Enhanced Token Optimization and Cost Reduction To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-11T23:42:15.199205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:42:15.199205Z digest=sha256:804552f070c7748382bad6d57d600feb6bf3d63a170c29a85e01fa058776fae4

Observation f0da3e70-0720-4af6-b3aa-05069aec29d5 · inbound

DNB-AI-Project at SemEval-2025 Task 5: An LLM-Ensemble Approach for Automated Subject Indexing cites this paper.

DNB-AI-Project at SemEval-2025 Task 5: An LLM-Ensemble Approach for Automated Subject Indexing To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-16T05:03:44.352631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T05:03:44.352631Z digest=sha256:0b86babae655dd7824761b190a0bfe9e0d2a4f9dabef0c0217a7abb3a52e5204

Observation bd2e68e9-e608-4969-9663-a67ad559edbb · inbound

ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution cites this paper.

ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models

Reference 140

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T13:58:58.925169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-16T13:58:58.627748Z digest=sha256:5b8ee095bca9e111b29068865aacd9dc6986d7ba69416d0e0d1bc88daa638a9d

Observation f9126600-b318-434d-823e-923f6398d965 · inbound

Sakana Fugu Technical Report cites this paper.

Sakana Fugu Technical Report To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models

Reference 175

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T06:39:36.880893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-26T14:22:37.596720Z digest=sha256:ddea363bbcd23971e40bead527d826d1e7c77f855cda1a4d8a2cc17c403ae5d2