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Paper Citation Record · LEDGER

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction

As of 15 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2501.06239.

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

pith.paper-citation-record.v1
2501.06239 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:36:45.186550Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

  • verified exact2
  • verified fuzzy13
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8013cab9-f93c-46ac-9cd7-a38c5831eb49 · outbound

This paper cites A systematic literature review on cyber threat intelligence sharing,.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction A systematic literature review on cyber threat intelligence sharing,

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-10T21:36:45.653982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.050371Z digest=sha256:2b0575f92f2774bbb31c737746f5ad91cac6cc52107a84599d4654d43fd6d99b

Observation e1ef1e8b-4b91-4cd5-9aa0-4eccfc69fa78 · outbound

This paper cites Ar- tificial intelligence methods for cyber threats intelligence,.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Ar- tificial intelligence methods for cyber threats intelligence,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-10T21:36:45.639664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.055585Z digest=sha256:6c5f46b3360eb8276dc61e39c0b85a3550fb1ec7c5cc74f80aa6fe420e7cb990

Observation fabf8d22-8672-4785-b2f2-34ef25b7b395 · outbound

This paper cites Artificial intelligence, cyber-threats and industry 4.0: Challenges and opportunities,.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Artificial intelligence, cyber-threats and industry 4.0: Challenges and opportunities,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-10T21:36:45.625567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.060828Z digest=sha256:4fccf0e3fa31f3acd21138373c3f67201a58bfcd24c272488d7e28a9304ebfff

Observation e948df5b-d401-4177-9d0d-b34c2e14dd92 · outbound

This paper cites GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer

Reference 4

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no resolver link, observed 2026-08-10T21:36:45.065733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:36:45.065733Z digest=sha256:95127c757911ad0cf99749ce8d8aeec622e89ee826d3976d32e5f46c9a53dcf8

Observation f159ec2d-21f1-4449-bb9f-94e0ed44c62a · outbound

This paper cites Standardizing Cyber Threat Intelligence Information with the Structured Threat Information eXpression (STIX),.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Standardizing Cyber Threat Intelligence Information with the Structured Threat Information eXpression (STIX),

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-10T21:36:45.610433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.071374Z digest=sha256:f71d7cb2c8a66017084df50c994fc889d39424eb80360bfc229b46a45f85f16c

Observation 739404a6-1c7b-401d-a5d1-235071839a05 · outbound

This paper cites Information extraction: Past, present and future,.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Information extraction: Past, present and future,

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-10T21:36:45.596389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.076493Z digest=sha256:f3004fa1de9a7b7c9232266bd63bd9ac41e4ed7dad5721e981acda0f6a975d1d

Observation b4645ee0-7023-467a-bc30-4f62c80f17cc · outbound

This paper cites Information Extraction of Cybersecurity Concepts: An LSTM Approach,.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Information Extraction of Cybersecurity Concepts: An LSTM Approach,

Reference 7

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raw_fallback, observed 2026-08-10T21:36:45.581545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.082257Z digest=sha256:5a4a21986bb7ae56b500bb6ba3adf4c237e87a6419294ced501f2e1a42268620

Observation e0b727d8-2e43-4cf8-ac3b-3e00c0765fbc · outbound

This paper cites Automated Retrieval of ATT&CK Tactics and Techniques for Cyber Threat Reports.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Automated Retrieval of ATT&CK Tactics and Techniques for Cyber Threat Reports

Reference 8

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no resolver link, observed 2026-08-10T21:36:45.086812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:36:45.086812Z digest=sha256:045fee6e38f61bf97e13b287717dc554b12d7252a31d576b9fb5c88aa28eb6d3

Observation fc859a7e-6044-4622-95f6-7342dad4c963 · outbound

This paper cites Automated Extraction of Vulnerability Information for Home Computer Security,.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Automated Extraction of Vulnerability Information for Home Computer Security,

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-10T21:36:45.567300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.092049Z digest=sha256:f7f2787206daefeb9215657a420d80abd060198c1ec357d6a6cc53ff0c64a3c3

Observation 40e5cf10-853b-43de-8a9a-3e3cff9a4c32 · outbound

This paper cites A Self-Attention-Based Approach for Named Entity Recognition in Cybersecurity,.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction A Self-Attention-Based Approach for Named Entity Recognition in Cybersecurity,

Reference 10

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raw_fallback, observed 2026-08-10T21:36:45.552624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.096837Z digest=sha256:b81580591dec46db79c70accd9eae70ba103cfe17e96d12b182fefdbbb51f5c5

Observation 38f5736a-2184-4068-aaac-3bbdf558ae74 · outbound

This paper cites SignalGP-Lite: Event Driven Genetic Programming Library for Large-Scale Artificial Life Applications.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction SignalGP-Lite: Event Driven Genetic Programming Library for Large-Scale Artificial Life Applications

Reference 11

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local_arxiv, observed 2026-08-10T21:36:45.433740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.101504Z digest=sha256:70f5c961fd24bd772afc6343fc096c57c8828a7618f8a5d4d0878eecf94dcc41

Observation 01312aa2-0e56-4072-a740-754e9dc54ee4 · outbound

This paper cites MTEB: Massive Text Embedding Benchmark.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction MTEB: Massive Text Embedding Benchmark

Reference 12

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unresolved
no resolver link, observed 2026-08-10T21:36:45.106586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:36:45.106586Z digest=sha256:f0282426d5355b71d14f3ff1e7b4723da535f05b82065043b05b3c0bee09efb0

Observation 275cf576-331d-40f6-bbeb-950b5f02564a · outbound

This paper cites Cy- ber Threat Intelligence Entity Extraction Based on Deep Learning and Field Knowledge Engineering,.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Cy- ber Threat Intelligence Entity Extraction Based on Deep Learning and Field Knowledge Engineering,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:36:45.536883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.111840Z digest=sha256:e570df9a0f7f5767b534594b00658edc4acea51712ca25d69b8ad14b4050d532

Observation ae9b2b63-9c1f-4d04-a0bf-9fc7f8679c87 · outbound

This paper cites CyNER: A Python Library for Cybersecurity Named Entity Recognition.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction CyNER: A Python Library for Cybersecurity Named Entity Recognition

Reference 14

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no resolver link, observed 2026-08-10T21:36:45.116400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:36:45.116400Z digest=sha256:b15d7af53bc41ed41aa3ed36cbb2bcec52bed1426cc0bf6c9ea18bd291ec68a5

Observation 34895583-21cd-477f-8af2-86c68b3cb6a8 · outbound

This paper cites CTI View: APT Threat Intelligence Analysis System,.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction CTI View: APT Threat Intelligence Analysis System,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:36:45.523093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.121054Z digest=sha256:ac4ed3aa82c08c2e58cb72b7b5d2f76225f24b74b9064b48d4b839ff77ccd318

Observation df2c96c4-2d30-4f8e-85f3-123d8f3b388e · outbound

This paper cites CDTier: A Chinese Dataset of Threat Intelligence Entity Relation- ships,.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction CDTier: A Chinese Dataset of Threat Intelligence Entity Relation- ships,

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-10T21:36:45.509381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.125689Z digest=sha256:096d7dbe40364bceabb772224616f4c482ab50fe3dc8417ec6baf9c30334862e

Observation 63bbcc2a-00fc-4d69-8abb-85511d7644cd · outbound

This paper cites STIXnet: A Novel and Modular Solution for Extracting All STIX Objects in CTI Reports.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction STIXnet: A Novel and Modular Solution for Extracting All STIX Objects in CTI Reports

Reference 17

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local_arxiv, observed 2026-08-10T21:36:45.382685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.130436Z digest=sha256:f4632c3a92aae21a32f482d7fc435a952176ca0d6eacd194cb7aacffa4f28685

Observation e479d9a1-2cd8-4907-b7c7-6b8b4e5d92e7 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction LLaMA: Open and Efficient Foundation Language Models

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:36:45.135270Z digest=sha256:ca2dcf25221cade8bbee99f3b6a71ef52fb8dd3fb072b6a1f0456ad359ff8de7

Observation 874ed71b-df34-4750-ba83-ccb6ebd65e40 · outbound

This paper cites Coherent driving of direct and indirect excitons in a quantum dot molecule.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Coherent driving of direct and indirect excitons in a quantum dot molecule

Reference 19

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verified exact
local_arxiv, observed 2026-08-10T21:36:45.346995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.140034Z digest=sha256:2221ff91b39fddd11517aa0c5517137dbfe6a065b05069784f50c7c0859e5fb4

Observation c307c868-58a5-4eee-a3d3-81305be6db9e · outbound

This paper cites Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Reference 20

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no resolver link, observed 2026-08-10T21:36:45.144884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:36:45.144884Z digest=sha256:0de1233f39d27301802783fe06724dc43a897570cda02285ee6885742c12169b

Observation dbf8b9a9-1661-4343-8e67-0a19918852a5 · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Scaling Instruction-Finetuned Language Models

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:36:45.149698Z digest=sha256:c86211f06b3f5b7615937ec1f457036ec85b1293774017a09abf35e0bc8d3197

Observation 19f86e31-f56f-41e5-b07d-76982bbf289d · outbound

This paper cites First Detection of the BAO Signal from Early DESI Data.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction First Detection of the BAO Signal from Early DESI Data

Reference 22

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no resolver link, observed 2026-08-10T21:36:45.155629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:36:45.155629Z digest=sha256:173e003ebaf7a1d15a7bd16f9d09d8c32f8244d215b87390a8c37c85d76bb8ab

Observation b5c93853-f208-4dc6-b445-e55041342d2c · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Code Llama: Open Foundation Models for Code

Reference 23

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no resolver link, observed 2026-08-10T21:36:45.160503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:36:45.160503Z digest=sha256:f216efc479e89caee7abed860fa7c6e95a9552b9d0316d3ef0130e784e8a5bf8

Observation 2a33aa6c-e4ab-413f-8937-371aa35330f6 · outbound

This paper cites The asymptotic formulae of sums of two smooth squares for divisor function.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction The asymptotic formulae of sums of two smooth squares for divisor function

Reference 24

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local_arxiv, observed 2026-08-10T21:36:45.263768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.166389Z digest=sha256:86e163fd7bf5e6bf62f30dc393e6a1c1045bb33566a990c1427233da6681803b

Observation ccb2f6e1-e068-4725-8eb6-78425f9130fd · outbound

This paper cites C-Pack: Packaged Resources To Advance General Chinese Embedding,.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction C-Pack: Packaged Resources To Advance General Chinese Embedding,

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-10T21:36:45.494385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.171292Z digest=sha256:401c27afbe8cf323287ae40b9cb580b655535a20491bfde948b2ed1ecc600e67

Observation ff098b5f-8bb4-4ae0-a3f7-c2d2ff62b7a1 · outbound

This paper cites In Defense of Cross-Encoders for Zero-Shot Retrieval.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction In Defense of Cross-Encoders for Zero-Shot Retrieval

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:36:45.176453Z digest=sha256:7e0efc440fef6367bd0bd3d36c34afbc56171b9ecb44346db39611492a6c3112

Observation c9659bb4-6d27-498a-b307-d4e10e20a274 · outbound

This paper cites Natural language processing in the era of large language models,.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction Natural language processing in the era of large language models,

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-10T21:36:45.479729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:36:45.181610Z digest=sha256:235b76f9df819152698bfd0fb681a8ad51b8393ff589bc929a07799a5d5662e7

Observation 5ee596d2-8933-468b-855d-7af07fcd1ab4 · outbound

This paper cites An Empirical Study of LLM-as-a-Judge for LLM Evaluation: Fine-tuned Judge Model is not a General Substitute for GPT-4.

Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction An Empirical Study of LLM-as-a-Judge for LLM Evaluation: Fine-tuned Judge Model is not a General Substitute for GPT-4

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:36:45.186550Z digest=sha256:6b1f362313d561c3a99babbcfe4ee66c0a08594dcc7bd7595f66b7a3038a7abc

Pith citing papers

No inbound Pith citation observations are available.