Paper Citation Record · LEDGER

Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2408.08902.

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

pith.paper-citation-record.v1
2408.08902 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 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 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:23:50.964463Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T05:27:40.493785Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 9d2960c3-7e04-474d-925f-887f0ba58455 · inbound

LLM-based event log analysis techniques: A survey cites this paper.

LLM-based event log analysis techniques: A survey Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-09T18:11:46.593577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99d16913-392a-40ca-8992-453dc67c7ea4 · inbound

Foundation Models for Anomaly Detection: Vision and Challenges cites this paper.

Foundation Models for Anomaly Detection: Vision and Challenges Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T16:34:14.373063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d5c3832-1eb3-4d92-8e0c-3fe51ac4421d · inbound

Exploring the Role of Large Language Models in Cybersecurity: A Systematic Survey cites this paper.

Exploring the Role of Large Language Models in Cybersecurity: A Systematic Survey Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T11:23:50.964463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbe5afb5-4d86-4e18-8a8d-5bbc872b76fb · inbound

Security of Internet of Agents: Attacks and Countermeasures cites this paper.

Security of Internet of Agents: Attacks and Countermeasures Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T22:26:17.892533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48288b06-bbf5-4aa9-a29d-9bad12234f98 · inbound

AD-AGENT: A Multi-agent Framework for End-to-end Anomaly Detection cites this paper.

AD-AGENT: A Multi-agent Framework for End-to-end Anomaly Detection Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T20:34:14.462844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39c099af-ec2d-4d2c-ba68-72ce7c97c9bd · inbound

Forewarned is Forearmed: A Survey on Large Language Model-based Agents in Autonomous Cyberattacks cites this paper.

Forewarned is Forearmed: A Survey on Large Language Model-based Agents in Autonomous Cyberattacks Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 177

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:59.565702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0487178-4a71-49f9-a812-7541ebb2f14e · inbound

SimViews: An Interactive Multi-Agent System Simulating Visitor-to-Visitor Conversational Patterns to Present Diverse Perspectives of Artifacts in Virtual Museums cites this paper.

SimViews: An Interactive Multi-Agent System Simulating Visitor-to-Visitor Conversational Patterns to Present Diverse Perspectives of Artifacts in Virtual Museums Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-05T21:58:52.641077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b7ae75d-fce7-466e-894d-06e102f35929 · inbound

ISACL: Internal State Analyzer for Copyrighted Training Data Leakage cites this paper.

ISACL: Internal State Analyzer for Copyrighted Training Data Leakage Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-05T16:50:26.401305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 924210bc-0c81-4f4f-be6d-26a113cd38e1 · inbound

Insight-LLM: LLM-enhanced Multi-view Fusion in Insider Threat Detection cites this paper.

Insight-LLM: LLM-enhanced Multi-view Fusion in Insider Threat Detection Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-05T12:34:44.921197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ece8b934-a61a-459b-aa41-34c914fd4096 · inbound

Large Language Models for Security Operations Centers: A Comprehensive Survey cites this paper.

Large Language Models for Security Operations Centers: A Comprehensive Survey Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 210

Resolution: unresolved; no resolver link, observed 2026-08-04T17:32:21.432594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09a68c78-ebc7-4c3b-b54d-ae76556ab13b · inbound

From Spark to Fire: Modeling and Mitigating Error Cascades in LLM-Based Multi-Agent Collaboration cites this paper.

From Spark to Fire: Modeling and Mitigating Error Cascades in LLM-Based Multi-Agent Collaboration Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-15T16:40:10.634987Z

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.

Observation c9b0eace-5d7a-46f4-be61-96fc4aacc6f9 · inbound

Retrieval-Augmented LLMs for Security Incident Analysis cites this paper.

Retrieval-Augmented LLMs for Security Incident Analysis Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-15T08:30:17.500719Z

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.

Observation e33bd8ca-5c29-4bc9-91b6-6ea85bc542cf · inbound

LLM4Log: A Systematic Review of Large Language Model-based Log Analysis cites this paper.

LLM4Log: A Systematic Review of Large Language Model-based Log Analysis Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 156

Resolution: verified exact; arxiv_id, observed 2026-05-15T08:25:19.238487Z

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.

Observation ecaf224e-3920-4030-824b-2a5a4fb94ffc · inbound

LLM4Log: A Systematic Review of Large Language Model-based Log Analysis cites this paper.

LLM4Log: A Systematic Review of Large Language Model-based Log Analysis Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 156

Resolution: verified exact; arxiv_id, observed 2026-05-21T10:04:06.606637Z

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.

Observation 2fad91fa-97c8-4169-bcd2-f21bfe1590a8 · inbound

AI-Driven Security Alert Screening and Alert Fatigue Mitigation in Security Operations Centers: A Comprehensive Survey cites this paper.

AI-Driven Security Alert Screening and Alert Fatigue Mitigation in Security Operations Centers: A Comprehensive Survey Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 137

Resolution: verified exact; arxiv_id, observed 2026-05-12T00:51:14.719190Z

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.

Observation a196b572-7776-4bbc-9762-08e810cab7a3 · inbound

Benchmarking and Exploring the Capabilities of LLMs for Attack Investigations cites this paper.

Benchmarking and Exploring the Capabilities of LLMs for Attack Investigations Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-07-03T05:27:40.495035Z

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.

Observation 638e8d8e-111a-49ac-b0eb-4ce14d1eb327 · inbound

Minos: A Multi-Agent Collaborative Framework for Provenance-Based Backward Tracking cites this paper.

Minos: A Multi-Agent Collaborative Framework for Provenance-Based Backward Tracking Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T11:46:54.838927Z

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.

Observation 44ad6d21-94f7-47b1-b9c7-72acdf0a1d7b · inbound

Adversarial Attacks in Multi-Agent LLM Pipelines: Unveiling Structural Vulnerabilities in Agentic AI Architectures cites this paper.

Adversarial Attacks in Multi-Agent LLM Pipelines: Unveiling Structural Vulnerabilities in Agentic AI Architectures Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T15:21:10.166487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.