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Paper Citation Record · LEDGER

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications

As of 10 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2506.10467.

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

pith.paper-citation-record.v1
2506.10467 v4

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:28:48.258906Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T03:14:38.619889Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T03:24:12.545203Z

Reference resolution

25 of 25 outbound references displayed

  • verified exact0
  • verified fuzzy23
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c7b03a2a-da06-4992-8925-23ed81e11c53 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T04:28:45.058427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:28:45.058427Z digest=sha256:015379aeaecb193704d2db546932cc2f4bf6c1cddd02f67e80083e7e8d2b8370

Observation 5d0323fb-16af-4a7f-8fd3-bae9641167ad · outbound

This paper cites Implications of new reasoning capabilities for science and security: Results from a quick initial study,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Implications of new reasoning capabilities for science and security: Results from a quick initial study,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:54.129611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:45.168313Z digest=sha256:87e5a4d0550b75668bb77c7bdc142a9c3df732e2354a6f93bfb5361fa04b53f9

Observation f6dfeb7e-79fd-416b-985e-b4863a3c5a91 · outbound

This paper cites 2024 AIME II,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications 2024 AIME II,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:53.883709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:45.310783Z digest=sha256:fd79f280e58fdc15b76c95a8a6dd65c1505e9a379799bd082d250ada7b28a8d7

Observation 35ede401-6b3e-4baf-bc3a-5ce0fe997f21 · outbound

This paper cites OpenAI Introduces o3,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications OpenAI Introduces o3,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:53.696359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:45.437894Z digest=sha256:42f886c643a2c98ac0de4b61a4ddb6e8d77219ff81fa47277d47d76fa8cf75f3

Observation fceef3ef-61f9-4797-bda4-97c2e710d614 · outbound

This paper cites Conceptual model interpreter for Large Language Models,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Conceptual model interpreter for Large Language Models,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:53.492578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:45.586757Z digest=sha256:181e59bf731488a4fb961aa807942c8b2791be80e525563eedbf4018c5d4e8fe

Observation 3c3d0618-ddf4-44cf-96f7-db86771ea1c3 · outbound

This paper cites Multi-Agent Systems: A Survey About Its Components, Framework and Workflow,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Multi-Agent Systems: A Survey About Its Components, Framework and Workflow,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:53.213893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:45.680924Z digest=sha256:c637d836b05cfc20fff484baf20a08c17cea0e13a0c1110b88b6bad9ebf61b1c

Observation 7c3c6c9f-4d35-434a-889c-9b0a5fc4712f · outbound

This paper cites A survey of the consensus for multi-agent systems,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications A survey of the consensus for multi-agent systems,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:52.924082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:45.807776Z digest=sha256:cad30234e1bb2f9d67706d56efb6318b21e760e295f99f9619ee9d2b0268afc7

Observation 0fe76d46-f61d-445d-a7ab-756df68184b0 · outbound

This paper cites A Survey of LLM- based Agents: Theories, Technologies, Applications and Suggestions,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications A Survey of LLM- based Agents: Theories, Technologies, Applications and Suggestions,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:52.702079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:45.946762Z digest=sha256:da2733dacce3f61dd9e5b00e14409a67f459857ff29dae46cfb6c5ea565df0d9

Observation 337ede23-bee2-4d2d-905c-1234a057d7e5 · outbound

This paper cites Large Language Model Based Multi-agents: A Survey of Progress and Challenges,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Large Language Model Based Multi-agents: A Survey of Progress and Challenges,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:52.396006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:46.142591Z digest=sha256:d83e5708b2aae5b7c3363ca69e38fc21528ce475cc59245e801503295fb992fe

Observation bcea0ac0-0c00-4be5-89c5-cafabf9be43c · outbound

This paper cites Large language models (LLMs): survey, technical frame- works, and future challenges,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Large language models (LLMs): survey, technical frame- works, and future challenges,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:52.136993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:46.289333Z digest=sha256:4cc3ab7cc64c3ad1b9aae29a2f7e4c014f802162b5432b22d4b17487b7281d95

Observation 5b106f92-bf38-497c-900c-dfe640a5a4c8 · outbound

This paper cites Chatgpt: A comprehensive review on background, applica- tions, key challenges, bias, ethics, limitations and future scope,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Chatgpt: A comprehensive review on background, applica- tions, key challenges, bias, ethics, limitations and future scope,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:51.912585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:46.407115Z digest=sha256:10cb7bd85403bf5151095c6a1efd69cccb664b585b4c626aad4712bd2287e994

Observation 2b1236f5-5ba1-45e3-af53-5efa3220ce69 · outbound

This paper cites Rothman, Transformers for Natural Language Processing.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Rothman, Transformers for Natural Language Processing

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:51.710200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:46.557636Z digest=sha256:b997348cf95767d4a4da4766c5e0e07517990a45122f4cac0dfa7154ecc2c672

Observation ade27d42-6630-4d01-9ed5-737e0b875459 · outbound

This paper cites Attention is all you need,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Attention is all you need,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:51.417518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:46.653485Z digest=sha256:ca95d5260299dfcac54caede01d1722a765164ec219b15e7582e1b09adaa528b

Observation dc7a2591-da29-4ff6-8cf4-24aaf1ca3299 · outbound

This paper cites Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T04:28:46.787064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:28:46.787064Z digest=sha256:7c30edbee297c499a5cc208ac66e39b8667c2bdb366022b47c447a57625d709f

Observation 4c93aaad-f9b4-4b58-9b7e-be0cea1ece33 · outbound

This paper cites ReCEval: Evaluating Reasoning Chains via Correctness and Informativeness,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications ReCEval: Evaluating Reasoning Chains via Correctness and Informativeness,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:51.116350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:46.938565Z digest=sha256:03175b0848e5d074eab49effb437e866c4f834efc3c40c84e274a3f41e9b5e15

Observation ecbf7053-2e52-4f0f-8c31-794fb3adcaac · outbound

This paper cites Constrained Reasoning Chains for Enhancing Theory-of-Mind in Large Language Models,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Constrained Reasoning Chains for Enhancing Theory-of-Mind in Large Language Models,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:50.853492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:47.080542Z digest=sha256:25b60abb2daba00596f252da93815f4826a51e2e29199a90da990088f7899347

Observation 32df6681-bff8-4d59-ba8d-cab8f350e707 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Self-Consistency Improves Chain of Thought Reasoning in Language Models,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:50.619955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:47.209731Z digest=sha256:1da1af0f174eebae49ac0d1ca2c10c954a00c2b42fd991c03625deea7d78c152

Observation 9fd51d0a-a080-4112-a50b-6c75a16bdc31 · outbound

This paper cites Evaluation of retrieval-augmented generation: A survey,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Evaluation of retrieval-augmented generation: A survey,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:50.364409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:47.329291Z digest=sha256:2a744728b00b6767c2b34f28d71885583db4f5faab7cb4e98cf2f0fac6053825

Observation 2b67ada8-c18d-4fdd-8dba-a31da4c3b53b · outbound

This paper cites CMAG: A Framework for Conceptual Model Augmented Generative Artificial Intelligence,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications CMAG: A Framework for Conceptual Model Augmented Generative Artificial Intelligence,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:50.097950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:47.509378Z digest=sha256:db851a33a279cf7649c37f60794ff087d539badd3d94f5150ff1d2325ee75ad2

Observation 6fcafdea-0e53-477a-91c7-53cd974c85e3 · outbound

This paper cites CyberMetric: A Benchmark Dataset based on Retrieval-Augmented Generation for Evaluating LLMs in Cybersecurity Knowledge,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications CyberMetric: A Benchmark Dataset based on Retrieval-Augmented Generation for Evaluating LLMs in Cybersecurity Knowledge,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:49.838058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:47.609078Z digest=sha256:f572acb5a086d3d71c15d00c905f6d8e12dc105bd8ef8bc9a5f8b92a290713a9

Observation 3e83d2d1-6d4c-46ba-b74d-c302a594cd40 · outbound

This paper cites SECURE: Benchmarking Large Language Models for Cybersecurity,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications SECURE: Benchmarking Large Language Models for Cybersecurity,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:49.574025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:47.749812Z digest=sha256:4b306bd2e26911ba46c52e90ffe41aeafbfbfbd2791b39394f2b5c7381f1def5

Observation 7e8973d4-7031-491c-a4f4-71e8d6cf788c · outbound

This paper cites CyberBench: A Multi-Task Benchmark for Evaluating Large Language Models in Cybersecurity,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications CyberBench: A Multi-Task Benchmark for Evaluating Large Language Models in Cybersecurity,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:49.363793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:47.872198Z digest=sha256:eaa07f8c2cc23b8b2136bf62fcb15406006fb3d856b8a2a7257ddb19741bcf4a

Observation 1350e14b-c67c-4210-bcd4-c8c5ee63499c · outbound

This paper cites CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:49.116933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:47.988994Z digest=sha256:c716835af4b55229b3ea46d6535a00d77221982b9945c4fd63e075f51cb4f98f

Observation 880f18d9-c3f7-4cc2-ba40-76aedd165f6e · outbound

This paper cites When LLMs meet cybersecurity: a systematic literature review,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications When LLMs meet cybersecurity: a systematic literature review,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:48.808209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:48.108537Z digest=sha256:ebeff1d814327c609e465af787b9004e906790451ae0226beba6234da264defa

Observation 3b1dfab2-2b4e-417d-a8f0-935b68663b2e · outbound

This paper cites Generative AI for Cyber Security: Analyzing the Potential of ChatGPT, DALL-E, and Other Models for Enhancing the Security Space,.

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications Generative AI for Cyber Security: Analyzing the Potential of ChatGPT, DALL-E, and Other Models for Enhancing the Security Space,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:48.565153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:28:48.258906Z digest=sha256:d4802e4661ef8abf1ac49858b6a16bcfbd6bf6f8b998884ebc2f42f125fe8a98

Pith citing papers

Observation 0a763ab4-4a02-4fa1-923a-1d7390d5aa68 · inbound

MAS-Lab: A Specification-Driven Validation Framework for Reliable Multi-Agent Systems cites this paper.

MAS-Lab: A Specification-Driven Validation Framework for Reliable Multi-Agent Systems Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-06-30T03:24:12.546507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T03:14:38.619889Z digest=sha256:288321b97c29d0f20a7b282785a4037d19b1ab95416649e060d5539991cd7391