Paper Citation Record · LEDGER

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI

As of 20 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.18243.

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

pith.paper-citation-record.v1
2607.18243 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T15:21:34.526438Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

verified exact0
verified fuzzy0
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0dfdd192-d198-404c-a5b7-0c98dc3a86c0 · outbound

This paper cites Gartner predicts over 40% of agentic AI projects will be canceled by end of 2027,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Gartner predicts over 40% of agentic AI projects will be canceled by end of 2027,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.421389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6f8b905-0e96-4e8e-afae-6275e975d72f · outbound

This paper cites Sok: The attack surface of agentic ai – tools, and autonomy,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Sok: The attack surface of agentic ai – tools, and autonomy,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.426653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59532598-e895-47e7-8652-e8676d38000b · outbound

This paper cites A new accident model for engineering safer systems,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI A new accident model for engineering safer systems,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.431349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c01e1243-998d-4d64-8cd3-46a8e8ae2cde · outbound

This paper cites STPA-SafeSec:Safetyandsecurityanalysisforcyber-physicalsystems,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI STPA-SafeSec:Safetyandsecurityanalysisforcyber-physicalsystems,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.436201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3733ca23-b8ad-43af-97b1-0beb8a4f3368 · outbound

This paper cites Optimization of conditional value-at-risk,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Optimization of conditional value-at-risk,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.440808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbec004a-c3a9-4f1c-8106-a991236c9324 · outbound

This paper cites An adversarial risk analysis framework for cyber- security,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI An adversarial risk analysis framework for cyber- security,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.445516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4677830-2234-4f19-92f9-7ba6c99774bc · outbound

This paper cites Attack–defense trees,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Attack–defense trees,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.450853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93a7d6a0-002b-492b-8e36-00f6c50bb79f · outbound

This paper cites DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.454882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54258d8b-581d-4cb5-8954-8fb782cff6fd · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.459645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d55104db-1156-44ab-8e49-edc859258529 · outbound

This paper cites MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.464015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c82a6a0a-6e97-4af6-93e7-8c68d4f082ec · outbound

This paper cites Why Do Multi-Agent LLM Systems Fail?.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Why Do Multi-Agent LLM Systems Fail?

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.468309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2a096eb-217e-4b31-a983-5a8dbe3379a6 · outbound

This paper cites Coherent measures of risk,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Coherent measures of risk,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.472980Z

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Unavailable: canonical work link unavailable.

Observation 19445fc2-e8c4-40a8-92a7-907ff824644f · outbound

This paper cites Estimationofsmallfailureprobabilitiesinhigh dimensions by subset simulation,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Estimationofsmallfailureprobabilitiesinhigh dimensions by subset simulation,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.477348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18caa138-fa8c-4170-8a2e-acd0acbb0ede · outbound

This paper cites Catastrophic cascade of failures in interdependent networks,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Catastrophic cascade of failures in interdependent networks,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.481497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3888153-9b25-47aa-87e2-a73b63b22cd9 · outbound

This paper cites AgentSpec: Customizable Runtime Enforcement for Safe and Reliable LLM Agents.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI AgentSpec: Customizable Runtime Enforcement for Safe and Reliable LLM Agents

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.486117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0398280a-df8d-4314-954a-87796ff33505 · outbound

This paper cites Pro2guard: Proactive runtime enforcement of LLM agent safety via probabilistic model checking,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Pro2guard: Proactive runtime enforcement of LLM agent safety via probabilistic model checking,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.490982Z

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Unavailable: canonical work link unavailable.

Observation 4a5e17fb-2fec-46f5-8960-c4c37092caf7 · outbound

This paper cites Defeating Prompt Injections by Design.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Defeating Prompt Injections by Design

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.495095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8916d11-4b2e-4943-a39e-cd3d441f57eb · outbound

This paper cites IsolateGPT: An Execution Isolation Architecture for LLM-Based Agentic Systems.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI IsolateGPT: An Execution Isolation Architecture for LLM-Based Agentic Systems

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.499697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d38891e-30ba-456a-993e-8c12dcf39d93 · outbound

This paper cites Progent: Securing AI Agents with Privilege Control.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Progent: Securing AI Agents with Privilege Control

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.504534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c7ef342-f662-441c-a046-a24ed6d27b45 · outbound

This paper cites Assurance of AI Systems From a Dependability Perspective.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Assurance of AI Systems From a Dependability Perspective

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.508973Z

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Unavailable: canonical work link unavailable.

Observation 6abe5ee2-95b0-430d-8bf8-1598e8f78d37 · outbound

This paper cites On the resilience of LLM-based multi-agent collaboration with faulty agents,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI On the resilience of LLM-based multi-agent collaboration with faulty agents,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.513701Z

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Observation 044c8124-566b-4a3f-88c3-cda760f47c7e · outbound

This paper cites Securing LLM workloads with NIST AI RMF in the internet of robotic things,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Securing LLM workloads with NIST AI RMF in the internet of robotic things,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.522292Z

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Unavailable: canonical work link unavailable.

Observation 435a977e-9ed7-412a-910c-a01195f6a082 · outbound

This paper cites Forge-bench: A threat-labeled dataset and digital twin framework for security evaluation of LLM-driven warehouse robots,.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI Forge-bench: A threat-labeled dataset and digital twin framework for security evaluation of LLM-driven warehouse robots,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.526438Z

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Unavailable: canonical work link unavailable.

Observation 7e19d699-e713-4330-b660-c3b30f8a819f · outbound

This paper cites 26202–26226.

From Agent Failure Paths to Quantified Residual Risk: A Compositional Framework for Resilient Agentic AI 26202–26226

Reference 267

Resolution: unresolved; no resolver link, observed 2026-08-02T15:21:34.518031Z

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Pith citing papers

No inbound Pith citation observations are available.