Paper Citation Record · LEDGER

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks

As of 18 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2607.25877.

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

pith.paper-citation-record.v1
2607.25877 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T01:16:48.777159Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

25 of 25 outbound references displayed

verified exact3
verified fuzzy0
unresolved21
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9f1533a2-d25e-424b-b7cc-21234249aa2c · outbound

This paper cites arXiv 2512.03816 (12 2025).

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks arXiv 2512.03816 (12 2025)

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:45.285209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aae7f797-09b9-4c6a-a747-95435d5d51b4 · outbound

This paper cites AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:45.415680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 357f78dd-a0fa-472b-be44-fd107f3a2473 · outbound

This paper cites Bayesian Uncertainty Propagation for Agentic RAG Pipelines: A Proof-of-Concept Study on Multi-Hop Question Answering.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks Bayesian Uncertainty Propagation for Agentic RAG Pipelines: A Proof-of-Concept Study on Multi-Hop Question Answering

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:45.490173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69d8b6d9-9840-4ef1-a208-368e484192fb · outbound

This paper cites UProp: Investigating the Uncertainty Propagation of LLMs in Multi-Step Agentic Decision-Making.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks UProp: Investigating the Uncertainty Propagation of LLMs in Multi-Step Agentic Decision-Making

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:45.634283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ebcf679-b5cc-4e6a-ba0c-94a0ae7b2065 · outbound

This paper cites Advanced Applications of Generative AI in Actuarial Science: Case Studies Beyond ChatGPT.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks Advanced Applications of Generative AI in Actuarial Science: Case Studies Beyond ChatGPT

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:45.791429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4fed2ce-63b1-48ea-b37f-51760d4259ca · outbound

This paper cites SentinelAgent: Graph-based Anomaly Detection in Multi-Agent Systems.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks SentinelAgent: Graph-based Anomaly Detection in Multi-Agent Systems

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:45.914436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06911641-987d-4e9a-ae82-a7692566b13a · outbound

This paper cites A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attribution.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attribution

Reference 7

Resolution: metadata mismatch; local_arxiv, observed 2026-08-01T01:22:03.450805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 40261f48-4896-45ed-9031-fc9973d1831a · outbound

This paper cites https://actuaries.org/paper/artificial-intelligence- governance-framework/ [Accessed 3/12/25] (2024).

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks https://actuaries.org/paper/artificial-intelligence- governance-framework/ [Accessed 3/12/25] (2024)

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:46.098823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cca7a2ae-4201-4bc0-9041-adbab6fcde5e · outbound

This paper cites Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV).

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:46.267444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cf67d4d-6eae-4110-be49-ab1e7d1592e1 · outbound

This paper cites Expert Systems with Applications42(4), 1917–1926 (2015).

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks Expert Systems with Applications42(4), 1917–1926 (2015)

Reference 10

Resolution: verified exact; doi, observed 2026-08-01T01:22:03.251169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9174e25c-7baa-4171-8df2-2e9ff7d87c82 · outbound

This paper cites Uncertainty Estimation in Autoregressive Structured Prediction.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks Uncertainty Estimation in Autoregressive Structured Prediction

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:46.509385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b16a827-e294-43c6-a911-fecf0fe15f3c · outbound

This paper cites https://ai.meta.com/blog/meta-llama-3-1/ [Ac- cessed 25/1/2026] (7 2024).

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks https://ai.meta.com/blog/meta-llama-3-1/ [Ac- cessed 25/1/2026] (7 2024)

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:46.671937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ce97143-f1ba-4de2-9cdb-c9c88504b287 · outbound

This paper cites In: Proceedings of the 31st ACM SIGKDD Conference on Knowl- edge Discovery and Data Mining V.2.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks In: Proceedings of the 31st ACM SIGKDD Conference on Knowl- edge Discovery and Data Mining V.2

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:46.785573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8328a0e1-a48f-49ce-9b36-e939db120c15 · outbound

This paper cites Extracting Probabilistic Knowledge from Large Language Models for Bayesian Network Parameterization.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks Extracting Probabilistic Knowledge from Large Language Models for Bayesian Network Parameterization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:46.956300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a371243-ed1b-4457-aae0-f11edc99db89 · outbound

This paper cites Applied Soft Computing52, 109–119 (3 2017).

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks Applied Soft Computing52, 109–119 (3 2017)

Reference 15

Resolution: verified exact; doi, observed 2026-08-01T01:22:02.977170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ac3e4a66-3fe5-4cbd-8c1b-6f6ff6799bd7 · outbound

This paper cites Risks10, 230 (12 2022).

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks Risks10, 230 (12 2022)

Reference 16

Resolution: verified exact; doi, observed 2026-08-01T01:22:02.852794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 059bf6f9-ff3c-4075-8568-8f9de9f2683c · outbound

This paper cites Morgan Kaufmann Pub- lishers Inc., San Francisco, USA (1988).

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks Morgan Kaufmann Pub- lishers Inc., San Francisco, USA (1988)

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:47.409734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7987ec2-1c72-4280-8dcb-811b7d238d7d · outbound

This paper cites https://huggingface.co/Qwen/Qwen2.5-7B-Instruct [Accessed 25/1/2026] (2025).

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks https://huggingface.co/Qwen/Qwen2.5-7B-Instruct [Accessed 25/1/2026] (2025)

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:47.585600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c256f97e-26db-45c6-b62d-1196228cf54a · outbound

This paper cites agentic ai: A con- ceptual taxonomy, applications and challenges.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks agentic ai: A con- ceptual taxonomy, applications and challenges

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:47.742765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 837705a9-7665-4792-99f8-b740161e885e · outbound

This paper cites Multi-Agent Collaboration Mechanisms: A Survey of LLMs.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks Multi-Agent Collaboration Mechanisms: A Survey of LLMs

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:47.890699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3098b744-4010-44da-9955-900b4e382a7d · outbound

This paper cites Frontiers of Computer Science18(12 2024).

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks Frontiers of Computer Science18(12 2024)

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:48.075194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77c38096-116a-44f7-a0f5-8c1fc61a23d9 · outbound

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

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:48.235794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 279eafd3-d4f2-4622-ade7-c72718327959 · outbound

This paper cites In: Proceedings of the ACM SIGSOFT Symposium on the Foundations of Software Engineering.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks In: Proceedings of the ACM SIGSOFT Symposium on the Foundations of Software Engineering

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:48.378125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ed98e35-8e61-46ec-9a71-3e9491b4a349 · outbound

This paper cites LLM-based Multi-Agent Systems: Techniques and Business Perspectives.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks LLM-based Multi-Agent Systems: Techniques and Business Perspectives

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:48.534406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8851f915-730e-496d-ae3e-6f56c7bf732d · outbound

This paper cites Survey on Evaluation of LLM-based Agents.

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks Survey on Evaluation of LLM-based Agents

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T01:16:48.777159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.