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Paper Citation Record · LEDGER

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

As of 19 August 2026, this Paper Citation Record lists 94 of 94 outbound references and 11 inbound Pith citation observations for arXiv:2508.01059.

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

pith.paper-citation-record.v1
2508.01059 v1

Coverage vector

measured 94 of 94 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:57:29.610113Z

measured 105 of 105 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T14:42:50.833204Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

94 of 94 outbound references displayed

  • verified exact1
  • verified fuzzy20
  • unresolved72
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 6d71bb92-94ca-4519-a6c3-5ee0a039dc93 · outbound

This paper cites https://www.first.org/cvss/v3.1/specification-document.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report https://www.first.org/cvss/v3.1/specification-document

Reference 1

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no resolver link, observed 2026-08-06T05:57:29.113886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.113886Z digest=sha256:f34fd98444e24dd9378f1c0b5e598e739821200d26649a1676d391411bfd668a

Observation 164685a2-094a-4c0e-9d28-340c3105add2 · outbound

This paper cites Phi-4 Technical Report.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Phi-4 Technical Report

Reference 2

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no resolver link, observed 2026-08-06T05:57:29.120192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.120192Z digest=sha256:6e4509daafec8f484702c8ea0dec6da02016318a1fa7394fa9238b4f65e3191b

Observation 1fccf4ec-840c-46b0-a0a3-f2083f8d3847 · outbound

This paper cites CTIBench: A benchmark for evaluating LLMs in cyber threat intelligence.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report CTIBench: A benchmark for evaluating LLMs in cyber threat intelligence

Reference 3

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unresolved
no resolver link, observed 2026-08-06T05:57:29.126082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.126082Z digest=sha256:a8f60d420518fa6885fd21d594c480994c26904956991031964e166c7057a08f

Observation 7327d8ff-52f3-41e7-954d-16872c996fa4 · outbound

This paper cites Cysecbert: A domain- adapted language model for the cybersecurity domain, 2022.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Cysecbert: A domain- adapted language model for the cybersecurity domain, 2022

Reference 4

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no resolver link, observed 2026-08-06T05:57:29.131216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.131216Z digest=sha256:8522527db084de814bfa4ab8b823cf7b3696ae21d755f7f9c4b025bc05a0a800

Observation 239ce2a5-1d50-4be4-b825-78d95d9876f4 · outbound

This paper cites Llama-nemotron: Efficient reasoning models.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Llama-nemotron: Efficient reasoning models

Reference 5

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no resolver link, observed 2026-08-06T05:57:29.136754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.136754Z digest=sha256:5ef1f01066055860a9154300b6d4ae546412a794961942e7a4c23f75b80f9b18

Observation d8b0ea9a-ed79-49d7-a65c-620cadc46e55 · outbound

This paper cites Language models are few-shot learners.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Language models are few-shot learners

Reference 6

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unresolved
no resolver link, observed 2026-08-06T05:57:29.142484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.142484Z digest=sha256:081b900ff20d026754dabc48c25129e15bc6f9c07a91798b35d837d4a2f44f5f

Observation b1c6e441-3429-479c-aaae-e850b88b5667 · outbound

This paper cites Common attack pattern enumerations and classifications (capec).

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Common attack pattern enumerations and classifications (capec)

Reference 7

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unresolved
no resolver link, observed 2026-08-06T05:57:29.148007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.148007Z digest=sha256:0f8cac103adc13c30f204984fc9a435c4cdb523f1f2aed91ff61584e9d848a78

Observation 31519e4a-f247-4d8f-930c-d7a71a89168b · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Evaluating Large Language Models Trained on Code

Reference 8

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no resolver link, observed 2026-08-06T05:57:29.154291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.154291Z digest=sha256:2cf7287145753234bc05f71a7dfcd843a5755b02371c5d061ed0c7efec372c2f

Observation fbd3c0ac-789b-464d-bf4b-3dce702147d8 · outbound

This paper cites MEDITRON-70B: Scaling Medical Pretraining for Large Language Models.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report MEDITRON-70B: Scaling Medical Pretraining for Large Language Models

Reference 9

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no resolver link, observed 2026-08-06T05:57:29.160461Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T05:57:29.160461Z digest=sha256:7bc1ee19dca97b7a98676235e212fe82999f1f38a92195b390d6b48ac8d88ddd

Observation 2ff82b81-6e20-4baf-9268-230bdd40be83 · outbound

This paper cites Kenderdine, J.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Kenderdine, J

Reference 10

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no resolver link, observed 2026-08-06T05:57:29.166630Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T05:57:29.166630Z digest=sha256:ee48a4d7c888c15bf61b31742570a339e870bfeb3a395772b885dd14df5108ac

Observation cd57f5ed-29a9-4a6a-bade-05f96bf2061e · outbound

This paper cites Scaling instruction-finetuned language models.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Scaling instruction-finetuned language models

Reference 11

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no resolver link, observed 2026-08-06T05:57:29.171888Z

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source=pdf_text observed=2026-08-06T05:57:29.171888Z digest=sha256:146941206c350908198462cca52c8df739d65198d00d2fc00ae660787e5934a4

Observation 83e01279-173f-47c5-8788-cefa8d48057b · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Training Verifiers to Solve Math Word Problems

Reference 12

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no resolver link, observed 2026-08-06T05:57:29.178051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.178051Z digest=sha256:f0bdbf74d9d4dc2509109efac09348f27bad088beb65f2423bc17b32828a7b3f

Observation b226be3a-9cd0-4c27-afda-91770ef748e7 · outbound

This paper cites Saullm-54b & saullm-141b: Scaling up domain adaptation for the legal domain.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Saullm-54b & saullm-141b: Scaling up domain adaptation for the legal domain

Reference 13

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no resolver link, observed 2026-08-06T05:57:29.183633Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T05:57:29.183633Z digest=sha256:b7fffe2f21744f02320fed55a4adc6fbd0b94f8e2abc0e60ff6c0b154633c28a

Observation fedad265-1970-492f-be16-bdbca22c803d · outbound

This paper cites SaulLM-7B: A pioneering Large Language Model for Law.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report SaulLM-7B: A pioneering Large Language Model for Law

Reference 14

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no resolver link, observed 2026-08-06T05:57:29.188856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.188856Z digest=sha256:e34285ae4b752ba2b968b398959097be95b0b6d8bbf05fd8047d46c8f7d00c4d

Observation ee83e362-733c-433e-ae85-0ef3c2ffa803 · outbound

This paper cites AI for DevSecOps, DeepHat.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report AI for DevSecOps, DeepHat

Reference 15

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no resolver link, observed 2026-08-06T05:57:29.194152Z

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source=pdf_text observed=2026-08-06T05:57:29.194152Z digest=sha256:9e950f797d80c2d614189828f7ce087161d500e7d47aedf93f6e605287daff88

Observation 70783106-1df8-41a5-9109-25201336718b · outbound

This paper cites Attacker: to- wards enhancing cyber-attack attribution with a named entity recognition dataset.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Attacker: to- wards enhancing cyber-attack attribution with a named entity recognition dataset

Reference 16

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unresolved
no resolver link, observed 2026-08-06T05:57:29.199443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.199443Z digest=sha256:8cdd753f8e766c278a0f4d054672024bd060524663f043c4f884785ef0689c9f

Observation 5bf95539-4270-48b2-a4de-096767f5e61c · outbound

This paper cites Investigating data contamination in modern benchmarks for large language models.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Investigating data contamination in modern benchmarks for large language models

Reference 17

Resolution
verified exact
doi, observed 2026-08-06T05:57:29.676373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.203880Z digest=sha256:64b15b1e414267cc25d159e84147b54f472de37695ad12b8433cdc3dbac058da

Observation 7d65bb07-26ce-4303-95c2-c1163975e96b · outbound

This paper cites Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Reference 18

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no resolver link, observed 2026-08-06T05:57:29.210496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.210496Z digest=sha256:b4cb109df975079c4d5e2999333f1690d87702b10ec76065efd15eac2e2e70f6

Observation 70d32098-702f-495e-9f47-24ab2b459924 · outbound

This paper cites General Data Protection Regulation (GDPR).

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report General Data Protection Regulation (GDPR)

Reference 19

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no resolver link, observed 2026-08-06T05:57:29.215862Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T05:57:29.215862Z digest=sha256:0ac69e49c740c5d455be32884b4a5a02b73aa1a38e1d884af964da18edf20e72

Observation 1a031aad-b042-4a44-8e06-a23729619ee5 · outbound

This paper cites Does data contamination detection work (well) for LLMs? a survey and evaluation on detection assumptions.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Does data contamination detection work (well) for LLMs? a survey and evaluation on detection assumptions

Reference 20

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no resolver link, observed 2026-08-06T05:57:29.220860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.220860Z digest=sha256:4255f1a7a3f9307844af342aae005047f9378078e33aada57801e5814b438e1d

Observation 1d155af6-aae1-48b6-9396-f3180a5213da · outbound

This paper cites Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?

Reference 21

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no resolver link, observed 2026-08-06T05:57:29.226026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.226026Z digest=sha256:bcbff954a580a754f8eb445a949692712aa93a3bce2de066508317f50d08b30d

Observation 59a0e594-7a2a-497d-99ff-17af86ec0ec7 · outbound

This paper cites The Llama 3 Herd of Models.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report The Llama 3 Herd of Models

Reference 22

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unresolved
no resolver link, observed 2026-08-06T05:57:29.231054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.231054Z digest=sha256:6759be2ed68fcb88c4d3d75871bd5729f9dbe2de3881276cf9fd50cf0942ff3b

Observation 552e56c2-64e9-408b-b04b-301bcfcf2e40 · outbound

This paper cites OLMES: A Standard for Language Model Evaluations.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report OLMES: A Standard for Language Model Evaluations

Reference 23

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no resolver link, observed 2026-08-06T05:57:29.236081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.236081Z digest=sha256:29d27799373a78eb4e0807a4437a529542042b15c74b3af2a799b837c3377e05

Observation 5ffd6a8e-0069-445d-bcea-5500b4e0fd03 · outbound

This paper cites Legalbench: A collaboratively built benchmark for measuring legal reasoning in large language models.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Legalbench: A collaboratively built benchmark for measuring legal reasoning in large language models

Reference 24

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unresolved
no resolver link, observed 2026-08-06T05:57:29.241038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.241038Z digest=sha256:5e3664967d941b0aa2184117db3b56a4d91d1bb53dde0e9de86c1635eafd24ca

Observation b0559ffc-24f6-4420-84cf-08a24efc9289 · outbound

This paper cites Generative active adaptation for drifting and imbalanced network intrusion detection.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Generative active adaptation for drifting and imbalanced network intrusion detection

Reference 25

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no resolver link, observed 2026-08-06T05:57:29.245905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.245905Z digest=sha256:b2ff2a84a34b4bcdb4524d739d3740094476ad1773d0fa763834e9b57d96de86

Observation ccc0e538-2fb6-4a43-8eea-31fa208f5f09 · outbound

This paper cites Measuring massive multitask language understanding.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Measuring massive multitask language understanding

Reference 26

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unresolved
no resolver link, observed 2026-08-06T05:57:29.250728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.250728Z digest=sha256:6fbf3b4de4b847945cf1cc1a664c774384ccdbfa2fdf6f590fc3bb556e72b292

Observation a8c61335-10cf-4bbd-9d02-0dbbbd2bc1d2 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Measuring Mathematical Problem Solving With the MATH Dataset

Reference 27

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unresolved
no resolver link, observed 2026-08-06T05:57:29.255750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.255750Z digest=sha256:50f3eb36458c8dfe0d1723da48bf18ba4a80c2976e7822c4e586eab5c491ad9a

Observation 37ce261a-2b6b-47b6-838d-3850cf67bf48 · outbound

This paper cites Universal Language Model Fine-tuning for Text Classification.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Universal Language Model Fine-tuning for Text Classification

Reference 28

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no resolver link, observed 2026-08-06T05:57:29.261529Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T05:57:29.261529Z digest=sha256:5d12f61326f28be7ab886f4f6bd60a856854cfda163750604e65940cd8cf66c1

Observation 37cd68c2-f425-4b13-9467-5d994f3f5c2e · outbound

This paper cites GPT-4o System Card.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report GPT-4o System Card

Reference 29

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unresolved
no resolver link, observed 2026-08-06T05:57:29.266752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.266752Z digest=sha256:9ca252416aa5532077eaf2e38c3f5d33ba1febeff60287ee37a8174a9766d51e

Observation 0f1e94ae-9858-419d-8101-cc7efc2b17cb · outbound

This paper cites Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations

Reference 30

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unresolved
no resolver link, observed 2026-08-06T05:57:29.271933Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.271933Z digest=sha256:f60d07a6b5f9e3c72f03d335b61c66723e5148992463700f5c76cf15f6840813

Observation e0981503-d933-44b0-93d0-c4af45570e98 · outbound

This paper cites Smith, Iz Beltagy, and Hannaneh Hajishirzi.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Smith, Iz Beltagy, and Hannaneh Hajishirzi

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:57:31.485856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.277433Z digest=sha256:6cc231cff82489b14d6703102071bd96b95664c4be47d558c0bf1ae1e5de6d84

Observation 04195146-6dd6-489b-a72b-65bb0b77d16e · outbound

This paper cites Mistral 7B.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Mistral 7B

Reference 32

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unresolved
no resolver link, observed 2026-08-06T05:57:29.282596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.282596Z digest=sha256:a9fe7a545dbec0b6ad862134dcfb0b35c5b976bdfbd481acf1f6c332f299b4d7

Observation 9be3f8d5-f0cd-44cc-b0d7-fee8b646ddd3 · outbound

This paper cites SecBench: A Comprehensive Multi-Dimensional Benchmarking Dataset for LLMs in Cybersecurity.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report SecBench: A Comprehensive Multi-Dimensional Benchmarking Dataset for LLMs in Cybersecurity

Reference 33

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unresolved
no resolver link, observed 2026-08-06T05:57:29.288634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.288634Z digest=sha256:5b39668d99196e525bba788355d3d38b255ed9c584ce05f6e00e264d3d279313

Observation a121a20a-a356-4a00-90c6-dc99091c24da · outbound

This paper cites Guide to cyber threat information sharing.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Guide to cyber threat information sharing

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:57:31.467229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.294273Z digest=sha256:0b67cd90b55cce6075c2cf0a0cf6b378f926b9c3f666eee028cbf6c070142d8f

Observation c31a8e24-2375-4c8f-90ff-a3cba659464c · outbound

This paper cites Bag of Tricks for Efficient Text Classification.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Bag of Tricks for Efficient Text Classification

Reference 35

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unresolved
no resolver link, observed 2026-08-06T05:57:29.300269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.300269Z digest=sha256:1657131f14df41b37c85e4d66e91bf47689649d2aec3527f99faf16eb877370c

Observation 98a875d2-c69a-4696-a036-f0e13ab8ab2b · outbound

This paper cites Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report

Reference 36

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unresolved
no resolver link, observed 2026-08-06T05:57:29.305859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.305859Z digest=sha256:0679fe3a8adfab5af83735d8e6aaf63a6278b3a7ff3120a87e74f1a2c657ff1e

Observation 55fb5cca-272a-4f08-bc62-eb9e82bffc21 · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 37

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source=pdf_text observed=2026-08-06T05:57:29.310777Z digest=sha256:c1799b56976b0504fd23b6d8390a8fcf3e9eb81d8ee23047555ad9fd05acfd5c

Observation 1c47ac1a-3d19-4119-9c0b-48578003e32f · outbound

This paper cites Platypus: Quick, Cheap, and Powerful Refinement of LLMs.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Platypus: Quick, Cheap, and Powerful Refinement of LLMs

Reference 38

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source=pdf_text observed=2026-08-06T05:57:29.316420Z digest=sha256:dfdaedc9b47c239e2876d0cc09593015d760795c54feb48af3f33e214336bdef

Observation cb074d78-bb09-4117-b417-4b62ca2337f2 · outbound

This paper cites Seceval: A comprehensive benchmark for evaluating cybersecurity knowledge of foundation models.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Seceval: A comprehensive benchmark for evaluating cybersecurity knowledge of foundation models

Reference 39

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source=pdf_text observed=2026-08-06T05:57:29.321512Z digest=sha256:eba11cb7be9312c5c5a9c724f3fb1cc4ce34a8a720624647dac4fc000202e31d

Observation 5faccb47-60d8-4e48-b6ec-f52ca20d486f · outbound

This paper cites Openorca: An open dataset of gpt augmented flan reasoning traces.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Openorca: An open dataset of gpt augmented flan reasoning traces

Reference 40

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raw_fallback, observed 2026-08-06T05:57:31.436155Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.326709Z digest=sha256:4dee0f21b3fb6f0f198ec49e0681ce288a1341db816240c645646dfbeb587152

Observation 5913bd84-b7ff-46dd-aac6-ee4ba7a18f80 · outbound

This paper cites SecQA: A Concise Question-Answering Dataset for Evaluating Large Language Models in Computer Security.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report SecQA: A Concise Question-Answering Dataset for Evaluating Large Language Models in Computer Security

Reference 41

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source=pdf_text observed=2026-08-06T05:57:29.331417Z digest=sha256:ade7514f76081618a6ed6d0d262652f43721e6d7140e4060907a1b8edef957dc

Observation 16855d17-5381-4e59-bb38-698c151d5baf · outbound

This paper cites HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal

Reference 42

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source=pdf_text observed=2026-08-06T05:57:29.337175Z digest=sha256:327aea3a95dc7d1984716a96fc44e541efd17ac4f59992b21b582beda52f4678

Observation 270db836-f084-450a-8e8a-74c04066bf31 · outbound

This paper cites an unresolved cited work.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Unresolved cited work

Reference 43

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.342830Z digest=sha256:a5f96707b97701b591b6ed4bf5f2271573f2ef7b62affb434ef831113680cf84

Observation e9b29bff-9d8d-4639-aff4-63b87c4e23ea · outbound

This paper cites Reducing conversational agents’ overconfidence through linguistic calibration.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Reducing conversational agents’ overconfidence through linguistic calibration

Reference 44

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raw_fallback, observed 2026-08-06T05:57:31.398334Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.347754Z digest=sha256:fbfeee652be3975d11774255ba9aa335d93125ddad57c310aaa241d1c77c7a28

Observation 5ca4ffda-1001-45bf-8a5c-b7dd191cd13f · outbound

This paper cites Large Language Models in Cybersecurity: State-of-the-Art.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Large Language Models in Cybersecurity: State-of-the-Art

Reference 45

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source=pdf_text observed=2026-08-06T05:57:29.352613Z digest=sha256:9eb5598414c7b040f1c2fbb6670eac9b35957ef147c2b4cf9281227676119baf

Observation b8d94cb2-eb7c-40fd-aaa1-a44456d7c991 · outbound

This paper cites Learning word representation for the cyber security vulnerability domain.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Learning word representation for the cyber security vulnerability domain

Reference 46

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source=pdf_text observed=2026-08-06T05:57:29.357490Z digest=sha256:585b2a7def08d6c338708c2b14620320a65de455f2e82f4cef82ca8a6ce62e6b

Observation 1da1cdb3-e897-4f61-86aa-4e0e0cbffbef · outbound

This paper cites Cross-domain language modeling: An empirical investigation.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Cross-domain language modeling: An empirical investigation

Reference 47

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raw_fallback, observed 2026-08-06T05:57:31.379297Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.362366Z digest=sha256:dab01393fa8493f1a78b0d78e020ac6c48ca6ce448a4c1b78e94143156bee20c

Observation 1d6b766b-b6c1-42e5-9e98-48e0d1d618f7 · outbound

This paper cites 2 OLMo 2 Furious.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report 2 OLMo 2 Furious

Reference 48

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source=pdf_text observed=2026-08-06T05:57:29.368001Z digest=sha256:7fee8500bb6bf843fbb991123edaaea11d2450da0328fa3e0b918a86dba5766f

Observation 628ca013-c23b-4f97-b3f9-a64a0c77d18c · outbound

This paper cites ChatGPT [large language model].

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report ChatGPT [large language model]

Reference 49

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.373023Z digest=sha256:200f420a5986fb4efb26804abcb2f0492fc39829fa5a4e32a5f5deaa2bb971aa

Observation c7899bb0-f20b-450d-99a1-29543fca5c9e · outbound

This paper cites Training language models to follow instructions with human feedback.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Training language models to follow instructions with human feedback

Reference 50

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source=pdf_text observed=2026-08-06T05:57:29.378378Z digest=sha256:c427a4fb7692d4fb9ea08389f509ad8d48daf9f313862e5d9dd47b5df8e93484

Observation f3439904-14c2-48a7-8565-e4a5bba0cf62 · outbound

This paper cites Training language models to follow instructions with human feedback.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Training language models to follow instructions with human feedback

Reference 51

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source=pdf_text observed=2026-08-06T05:57:29.383809Z digest=sha256:7b2e0b325a8ed6ea72d6f572ae89f45914578141c35a391eda655c7439e1a514

Observation 69414543-696a-4a8f-af3e-e47bca5b3d40 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Direct preference optimization: Your language model is secretly a reward model

Reference 52

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source=pdf_text observed=2026-08-06T05:57:29.388645Z digest=sha256:938caa34ced88c9a3d46dad306a0b3f3beedb7de95765fff755e1fdcd25dcf6b

Observation 5bf318ad-ccf6-45e5-951d-b03a7fc9c8fe · outbound

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

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Code Llama: Open Foundation Models for Code

Reference 53

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source=pdf_text observed=2026-08-06T05:57:29.393475Z digest=sha256:cf51f6f58e504756f79fb9c22fda58c0bd0de80e86d15d8076d7692957fb0288

Observation 1ace1373-e7ca-47a3-b740-b3bde90ffb06 · outbound

This paper cites PersonaGym: Evaluating Persona Agents and LLMs.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report PersonaGym: Evaluating Persona Agents and LLMs

Reference 54

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source=pdf_text observed=2026-08-06T05:57:29.399558Z digest=sha256:b2d9d842915c1d5ca58a842369ca50b96df318a5d2a06516259caac31913e91d

Observation cb3adb52-f766-4186-9fca-1eba64df3627 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Proximal Policy Optimization Algorithms

Reference 55

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source=pdf_text observed=2026-08-06T05:57:29.405188Z digest=sha256:c1a26ad2f732a203e87de73a3faf2008f6dae7c28e4e250a20c1c4edd45da28d

Observation 9d055963-d16d-46da-8812-ca78c1944b00 · outbound

This paper cites Lily-cybersecurity-7b-v0.2: A cybersecurity assistant.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Lily-cybersecurity-7b-v0.2: A cybersecurity assistant

Reference 56

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.410753Z digest=sha256:deb6ad59d762886977f7d192f2c0382be0a7f8a8a6fdb0f376e6e19b25ee2491

Observation 7ade8d88-28d7-4fda-a9ce-64d85180d883 · outbound

This paper cites Toward expert-level medical question answering with large language models.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Toward expert-level medical question answering with large language models

Reference 57

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raw_fallback, observed 2026-08-06T05:57:31.282599Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.422973Z digest=sha256:2113b30c6b5c0c3dc5af640e41feb0e218aef78c3b03573fe4851f0d698969d1

Observation d5d576da-86e5-4ff7-837a-cdeb6439cc0d · outbound

This paper cites Beyond the imitation game: Quantifying and extrapolating the capabilities of language models.Transactions on machine learning research, 2023.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Beyond the imitation game: Quantifying and extrapolating the capabilities of language models.Transactions on machine learning research, 2023

Reference 58

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source=pdf_text observed=2026-08-06T05:57:29.428455Z digest=sha256:4d6f6b736da5bb86ea83afca51eeb22f87927b5fe5c344009e8803d6daa6b63f

Observation 80e0fbaa-3664-4e0c-a22f-9c2d28597981 · outbound

This paper cites Strom, Andy Applebaum, Doug P.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Strom, Andy Applebaum, Doug P

Reference 59

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raw_fallback, observed 2026-08-06T05:57:31.245203Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.433988Z digest=sha256:88bf3c2100626affb09d7d226dfca7f07774657cdf385f6cbab7944095819da5

Observation efee2fd9-4243-4229-a399-8736cd928a69 · outbound

This paper cites Bertscore is unfair: On social bias in language model-based metrics for text generation, 2022.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Bertscore is unfair: On social bias in language model-based metrics for text generation, 2022

Reference 60

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.438838Z digest=sha256:27b17bf7a493e09afcf1bbf72c9255b9d2d2e280dbdccd66e508be204866d071

Observation 7dad229c-2e55-457a-840b-84c9f90a88d9 · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 61

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source=pdf_text observed=2026-08-06T05:57:29.443862Z digest=sha256:7c2f96f8d205e57b7e57a410521125b7e1816a86a6a56c6c2e5aa1012a388d1e

Observation caf99c50-dbcd-44e1-ab5b-ecd10c7cef1e · outbound

This paper cites Hashimoto.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Hashimoto

Reference 62

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.449607Z digest=sha256:b4dad343af034a8c4df18b632ffa0bff72a4ad95b02c7c51fbf7163f125585d2

Observation e6ec90fb-884d-4ce3-87ab-8170a09fb0d4 · outbound

This paper cites Gemma 3 Technical Report.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Gemma 3 Technical Report

Reference 63

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source=pdf_text observed=2026-08-06T05:57:29.454406Z digest=sha256:67f501aebf47418d51ab9a3f8fa7aef903b590a53f327610c43ab6fb261df548

Observation 9cec94e4-f46e-4b68-a23a-d38e2be36629 · outbound

This paper cites Cve ® – common vulnerabilities and exposures program.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Cve ® – common vulnerabilities and exposures program

Reference 64

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raw_fallback, observed 2026-08-06T05:57:31.193694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.459666Z digest=sha256:7af623239510bf490806b53e090a6de4d192a0003aee121d94ebbc77477a0562

Observation 659b32d4-f860-4940-ac50-59e70e333e8e · outbound

This paper cites Cybermetric: A benchmark dataset based on retrieval-augmented generation for evaluating llms in cybersecurity knowledge.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Cybermetric: A benchmark dataset based on retrieval-augmented generation for evaluating llms in cybersecurity knowledge

Reference 65

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source=pdf_text observed=2026-08-06T05:57:29.464792Z digest=sha256:8315298972aba56883e87d4ba9c6ff352dc1e315bd8a3ec88e3a1650052d9207

Observation 35a3de17-10cd-4cef-8619-7466bc060375 · outbound

This paper cites Cybermetric: a benchmark dataset based on retrieval-augmented generation for evaluating llms in cybersecurity knowledge.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Cybermetric: a benchmark dataset based on retrieval-augmented generation for evaluating llms in cybersecurity knowledge

Reference 66

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raw_fallback, observed 2026-08-06T05:57:31.172917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.469874Z digest=sha256:3ef79eae8a992cb6e72a71681c3af02b9da7b8c440db614366f60811f45b2153

Observation 1d2ecf6f-0e40-44ce-90fe-f70a96f66999 · outbound

This paper cites A comprehensive survey of hallucination mitigation techniques in large language models.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report A comprehensive survey of hallucination mitigation techniques in large language models

Reference 67

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raw_fallback, observed 2026-08-06T05:57:31.155540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.474795Z digest=sha256:497a793ffd56c3be02d866fc5df843a38118e5a6e0d946ded8b72cd24cd92f75

Observation 8bb53247-6f91-4dbe-add6-5244816e25c5 · outbound

This paper cites Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Reference 68

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source=pdf_text observed=2026-08-06T05:57:29.479428Z digest=sha256:7a31e616cb2519d939ab702af1da772bf5deb04849a7b112fe977549c825c9a0

Observation f3a8a792-db35-4a37-b4b5-5e93ca26b86f · outbound

This paper cites Smarter, better, faster, longer: A modern bidirectional encoder for fast, memory efficient, and long context finetuning and inference.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Smarter, better, faster, longer: A modern bidirectional encoder for fast, memory efficient, and long context finetuning and inference

Reference 69

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raw_fallback, observed 2026-08-06T05:57:31.138382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.484724Z digest=sha256:d9051beecd50e0ff7e79f345f11c1a03304cc4dd54d9df6884ac7819f93e3a76

Observation 7c74a78b-960b-4329-8904-9685cf7830eb · outbound

This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report WizardLM: Empowering large pre-trained language models to follow complex instructions

Reference 70

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T05:57:29.489808Z digest=sha256:e61c8382b1af47a77f4322e31260bd81727a54f81482cb525bc81f430dce1c7a

Observation 0984bda8-970d-414e-a28d-80c0a3f34bdb · outbound

This paper cites Benchmark Data Contamination of Large Language Models: A Survey.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Benchmark Data Contamination of Large Language Models: A Survey

Reference 71

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no resolver link, observed 2026-08-06T05:57:29.494966Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T05:57:29.494966Z digest=sha256:81aa4096adaa6d374dfd8ddfc83dfa82441a5a1bd1cb5b6f3ae4317b572193e8

Observation ae619409-9dbe-4511-ad77-b8af9e50b500 · outbound

This paper cites Large language models for cyber security: A systematic literature review.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Large language models for cyber security: A systematic literature review

Reference 72

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no resolver link, observed 2026-08-06T05:57:29.500181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.500181Z digest=sha256:ebbb0ac802122cfae63a8eba123fa968af8402d95657ade8f4c9757fb202320d

Observation 2f8fb4d0-95a0-483b-af0b-48214e9e5759 · outbound

This paper cites Qwen3 Technical Report.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Qwen3 Technical Report

Reference 73

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no resolver link, observed 2026-08-06T05:57:29.505886Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.505886Z digest=sha256:e06bda3f9a0da8eebb429ac5dbabbd1675a9af96ebc88a4b2f8e0f240b1ad5f4

Observation 8fca8ffb-2cd4-4adf-b168-b5219a677eb7 · outbound

This paper cites Rethinking Benchmark and Contamination for Language Models with Rephrased Samples.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 74

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no resolver link, observed 2026-08-06T05:57:29.511258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.511258Z digest=sha256:32d79e644d63df913853e2c68bcbf66fec4444f2aa4e0fbaf70088d0fdbc6247

Observation fd0c7f05-5ae4-4de5-a7f6-1ca1d35b65bf · outbound

This paper cites Primus: A pioneering collection of open-source datasets for cybersecurity llm training.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Primus: A pioneering collection of open-source datasets for cybersecurity llm training

Reference 75

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no resolver link, observed 2026-08-06T05:57:29.516581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.516581Z digest=sha256:7ee6c0367478927562d3985de955e5dbfa042036ff58be549ff632fb1ee86c01

Observation 063639a0-1e72-4497-a8a7-3174e901d29a · outbound

This paper cites Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models

Reference 76

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no resolver link, observed 2026-08-06T05:57:29.522003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.522003Z digest=sha256:a86017210306a25d80e36fd23edf098098715da6197db17b5df58793fa7e7f3f

Observation f46b9864-c8e7-4e90-be99-522aa90ba0de · outbound

This paper cites When LLMs Meet Cybersecurity: A Systematic Literature Review.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report When LLMs Meet Cybersecurity: A Systematic Literature Review

Reference 77

Resolution
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no resolver link, observed 2026-08-06T05:57:29.527208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.527208Z digest=sha256:85f8430428822fc693488ec4e40506767ae3df53080bbb672c8beb35449ebbd0

Observation 20ccf4f1-bef3-43c3-826c-365782f12126 · outbound

This paper cites When llms meet cybersecurity: A systematic literature review.Cybersecurity, 8(1):55, 2025.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report When llms meet cybersecurity: A systematic literature review.Cybersecurity, 8(1):55, 2025

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:57:31.121368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.532271Z digest=sha256:a6ebdb4de224285424480ed57996fd74eb38033337b5a473df928144c807d855

Observation c4e7580b-85ef-4b4e-9335-0d5da183fe7f · outbound

This paper cites Lima: Less is more for alignment.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Lima: Less is more for alignment

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:57:31.103796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.537198Z digest=sha256:1add743e2de852cd4c167235f147b668a2258eede215bb4fee54a62bb437d74f

Observation c0f1eef3-32fe-4796-9dc2-04fbe5f1c782 · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Instruction-Following Evaluation for Large Language Models

Reference 80

Resolution
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no resolver link, observed 2026-08-06T05:57:29.541936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.541936Z digest=sha256:17d160aa4f8b453e988ec87f38b706da164a2997f2fca16d365f04e5ef2a45ac

Observation eb227066-776e-4871-9d25-4ebd0fd78fc4 · outbound

This paper cites output as a JSON object.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report output as a JSON object

Reference 81

Resolution
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no resolver link, observed 2026-08-06T05:57:29.547334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:57:29.547334Z digest=sha256:99874ba6e51e59ee480a10f09e0dacf6f59fee31887f17e8bc47acc0fc6f7092

Observation aeb1f0b4-c72b-4ce7-b97b-55e14c581e7d · outbound

This paper cites an unresolved cited work.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Unresolved cited work

Reference 83

Resolution
unresolved
raw_fallback, observed 2026-08-06T05:57:31.084805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.552875Z digest=sha256:892289adb5f0656651ed826fac62242ad8954117a491f6354fcf1d3db78fd0ad

Observation 19ad239d-6182-4bfa-be94-638d91ff31b8 · outbound

This paper cites an unresolved cited work.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Unresolved cited work

Reference 84

Resolution
unresolved
raw_fallback, observed 2026-08-06T05:57:31.067370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.558321Z digest=sha256:8d094ed89a841ccbcf05aa80e24e64c3895bcda2ba200dfcbafc7aff94e631c7

Observation 9c3e3fdb-cdcd-474c-943c-88f0fb267594 · outbound

This paper cites an unresolved cited work.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Unresolved cited work

Reference 85

Resolution
unresolved
raw_fallback, observed 2026-08-06T05:57:31.049565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.563095Z digest=sha256:a9986a17bd356436cb16b02ccdc7b26bd6338b9d94eb7d8c013ac30d106298c4

Observation 3878fe27-6810-4ed0-a368-eb7a1bb19072 · outbound

This paper cites an unresolved cited work.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Unresolved cited work

Reference 86

Resolution
unresolved
raw_fallback, observed 2026-08-06T05:57:31.031971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.567900Z digest=sha256:441a2ae705f4720b8ce42f021e9f182b665e1e61dd6c4a22231fcb31d0ca9906

Observation 9ce49ac7-9387-4f15-9047-7aad55aa5edc · outbound

This paper cites an unresolved cited work.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Unresolved cited work

Reference 87

Resolution
unresolved
raw_fallback, observed 2026-08-06T05:57:31.015257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.572958Z digest=sha256:6abd7332b2b7482cd09b94a59d58d3e8a74d15e903428ce91a706493584a4631

Observation 09291b93-d015-4b1f-93af-f8a2ac589498 · outbound

This paper cites an unresolved cited work.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Unresolved cited work

Reference 88

Resolution
unresolved
raw_fallback, observed 2026-08-06T05:57:30.997184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.578046Z digest=sha256:ddcd80ef239170f84525f7d7931a3f0008c5642d01b714d75b2741c3ead43f60

Observation 1e5eacd0-4305-406a-be75-f5edbf049ef4 · outbound

This paper cites an unresolved cited work.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Unresolved cited work

Reference 89

Resolution
unresolved
raw_fallback, observed 2026-08-06T05:57:30.977059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.582824Z digest=sha256:9b48a89314ab016cdf8c26fa34e0fe3d4d6a7a84b5530b2018af77bab5fbb120

Observation c1419d84-2733-4cff-966e-1f796e7082dd · outbound

This paper cites an unresolved cited work.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Unresolved cited work

Reference 90

Resolution
unresolved
raw_fallback, observed 2026-08-06T05:57:30.957066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.588028Z digest=sha256:d413b3d6c4d7be1dc615c9349e9f538536ef5b96ac271d73626aa7c84056ca47

Observation 94140887-b28f-483b-ab13-a18ed8c5a1be · outbound

This paper cites an unresolved cited work.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Unresolved cited work

Reference 91

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unresolved
raw_fallback, observed 2026-08-06T05:57:30.939220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.592953Z digest=sha256:951c01c2182809e1345a5e7860a42c64f8bd7eea9aca832f6bea1a424e39d6eb

Observation ca2cbe9e-8c36-4fb8-9d39-8189ba580007 · outbound

This paper cites sandbox”, “policy.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report sandbox”, “policy

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:57:30.922859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.598148Z digest=sha256:ede1450799950c518148efb32b61e0a05f5109bed7e8b4fa7832d2d14cb46d07

Observation 52735b92-f072-4940-891b-c3db88dbdbc8 · outbound

This paper cites content":.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report content":

Reference 93

Resolution
malformed identifier
raw_fallback, observed 2026-08-06T05:57:30.906263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.603954Z digest=sha256:a71a7508a94be8aedf3f2eafc50d32bd89ce86524c13f026a8157632a39125d2

Observation 06f11264-c95d-4c22-8387-082c4bb859ad · outbound

This paper cites Respond to both names and maintain the identity at all times.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Respond to both names and maintain the identity at all times

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:57:30.888210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.610113Z digest=sha256:4c88ea473046c77df33bfdb7308a11ebc5bfc151bc38406e05dcd2e94489f95a

Observation e0a76c7f-8900-41a9-8c77-8c0602acf49c · outbound

This paper cites Fine-tuned on Mistral-7B-Instruct-v0.2 with 22,000 hand-crafted cybersecurity/hacking pairs.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Fine-tuned on Mistral-7B-Instruct-v0.2 with 22,000 hand-crafted cybersecurity/hacking pairs

Reference 2025

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:57:31.302808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T05:57:29.416089Z digest=sha256:10e86babbf3685eb61e3a2cc927d9d3b47d361b3d16201101d51e550ae9d1529

Pith citing papers

Observation 5e30a945-e436-4bce-a319-c3ebab8a2648 · inbound

Uncovering Vulnerabilities of LLM-Assisted Cyber Threat Intelligence cites this paper.

Uncovering Vulnerabilities of LLM-Assisted Cyber Threat Intelligence Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-04T14:42:50.833204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:42:50.833204Z digest=sha256:7eaccae5e96a23f4dc244f94ca8f8f7fcf61acaa521bb8a83a52581dc248bbee

Observation e53929c0-5a99-4d47-8bae-de32d42e5d2d · inbound

Toward Cybersecurity-Expert Small Language Models cites this paper.

Toward Cybersecurity-Expert Small Language Models Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

Reference 20

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unresolved
no resolver link, observed 2026-08-04T09:40:27.631283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:40:27.631283Z digest=sha256:ea9aebced04f785606f91cfbe6c37fa65a558eaed510a19df180c00ed4430d9c

Observation 068f988c-52e5-4efc-9fdc-96c9f8aefab7 · inbound

Test-Time Detoxification without Training or Learning Anything cites this paper.

Test-Time Detoxification without Training or Learning Anything Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

Reference 48

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unresolved
no resolver link, observed 2026-08-03T10:40:47.652225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:40:47.652225Z digest=sha256:9a4d8b7b10d6d046e67ce42e660e6287719c013d20155d89bafa37f3326e20cf

Observation 0ee53f36-3144-4772-b3a8-9ad385c8164e · inbound

Trust Me, Import This: Dependency Steering Attacks via Malicious Agent Skills cites this paper.

Trust Me, Import This: Dependency Steering Attacks via Malicious Agent Skills Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:56:27.301526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-12T03:49:49.484361Z digest=sha256:0c12a859356aa89ffd45f6cdb71827f898ef075266d25cea841d870654c1b015

Observation 19863e6b-184a-47d1-8acd-aed33766e1de · inbound

Threat Modelling using Domain-Adapted Language Models: Empirical Evaluation and Insights cites this paper.

Threat Modelling using Domain-Adapted Language Models: Empirical Evaluation and Insights Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:56:25.764269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-12T03:50:46.260450Z digest=sha256:6dd647e487cb29f4c81a467649a275551f78ef1eaa918580ca6cb6d84623cc78

Observation 955717c9-4b13-4954-a463-a81692fb14f6 · inbound

FAPO: Fully Automated Prompt Optimization of Multi-Step LLM Pipelines cites this paper.

FAPO: Fully Automated Prompt Optimization of Multi-Step LLM Pipelines Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-06-26T21:09:57.826993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-26T19:50:46.691071Z digest=sha256:4dc83c6dd9dc0c12a4fb464f153053eb4959c8e6d8c38bb16d71e3cd35367492

Observation 8cd630d2-dc92-4cce-9fee-1a14509791a3 · inbound

LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learning cites this paper.

LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learning Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

Reference 112

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:48:39.935601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-27T05:02:18.347642Z digest=sha256:057b1722795061f6031baa4cfbc31c572647f738254f7d5066620f072c180c97

Observation 5d9d519b-1b2a-4cd6-9fb1-dea2c8eac49c · inbound

Inherited Circuits, Learned Semantics: How Fine-Tuning Creates Evasion Vulnerabilities Invisible to Standard Evaluation cites this paper.

Inherited Circuits, Learned Semantics: How Fine-Tuning Creates Evasion Vulnerabilities Invisible to Standard Evaluation Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-07-04T14:29:53.640362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-26T03:46:22.192212Z digest=sha256:c8c323079e5d4487e128d8c3026f4cce28c81109253b466f6587aca0b0cd2745

Observation 91d4f039-5ec3-425b-b5d4-009fe9521240 · inbound

TACTIC-KG: Toward Small Agent Teams for Cyber Threat Intelligence Knowledge Graph Construction cites this paper.

TACTIC-KG: Toward Small Agent Teams for Cyber Threat Intelligence Knowledge Graph Construction Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

Reference 34

Resolution
unresolved
no resolver link, observed 2026-07-11T10:18:01.537693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T10:18:01.537693Z digest=sha256:fe4e890534895b6802f94bb12be686f33bee24ae2ef1d7d47bcbb1165c0080c8

Observation 9d56eae1-b37c-4843-9334-0c77cb4b9876 · inbound

Supervised Fine-Tuning vs. In-Context Learning: An Equilibrium Analysis of LLM Personalization under Congestion cites this paper.

Supervised Fine-Tuning vs. In-Context Learning: An Equilibrium Analysis of LLM Personalization under Congestion Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

Reference 105

Resolution
unresolved
no resolver link, observed 2026-08-02T02:24:43.663141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T02:24:43.663141Z digest=sha256:e962e054cb3eef5550d6af59edff1895e73ddb068ebbb7225b054a200aff728a

Observation 3dd60dc4-fa6f-46e7-8c5b-cc25238ae705 · inbound

Antares: Foundation Models for Agentic Vulnerability Localization cites this paper.

Antares: Foundation Models for Agentic Vulnerability Localization Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-04T07:50:50.742631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T07:50:50.742631Z digest=sha256:ba8ab4735bf992c6ac83e84428075a47d3093db2d233ca11fccf42ba0fdd0b02