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Paper Citation Record · LEDGER

Real-Time Detection and Repair of LLM Agent Failures

As of 20 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2608.02464.

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

pith.paper-citation-record.v1
2608.02464 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T06:55:00.757185Z

measured 33 of 33 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

33 of 33 outbound references displayed

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  • verified fuzzy0
  • unresolved33
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 94b2c4c9-e444-4da2-b938-5f1ab8d4c62b · outbound

This paper cites Xing, Hao Zhang, Joseph E.

Real-Time Detection and Repair of LLM Agent Failures Xing, Hao Zhang, Joseph E

Reference 1

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source=pdf_text observed=2026-08-04T06:54:58.076690Z digest=sha256:6f1e2bcfbb398d8e7c947987fee55ce8319b344183b1e383a4a8c0383c1d3f03

Observation 4abbe13b-a5ae-46a5-b138-b6cdda120d5d · outbound

This paper cites an unresolved cited work.

Real-Time Detection and Repair of LLM Agent Failures Unresolved cited work

Reference 2

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source=pdf_text observed=2026-08-04T06:54:58.120775Z digest=sha256:387f1a6dc6d0c0813a6c2941e97b912bdb805316ec772b74a5009d597608e7ab

Observation 883b5a28-b88f-478e-875a-23e8f80ab284 · outbound

This paper cites Nikiforov.Detection of Abrupt Changes: Theory and Application.

Real-Time Detection and Repair of LLM Agent Failures Nikiforov.Detection of Abrupt Changes: Theory and Application

Reference 3

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source=pdf_text observed=2026-08-04T06:54:58.176383Z digest=sha256:aab8c504e2ffe32cf66c45813447600c74f891bfed21ed79ad46d8f5db5724f0

Observation 213c54a7-147f-4a9e-8385-d3c8a032686c · outbound

This paper cites Anomaly detection: A survey.ACM Computing Surveys, 41(3):1–58, 2009.

Real-Time Detection and Repair of LLM Agent Failures Anomaly detection: A survey.ACM Computing Surveys, 41(3):1–58, 2009

Reference 4

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source=pdf_text observed=2026-08-04T06:54:58.228188Z digest=sha256:09165be0e949ab1f7d90396b75eef511d949f40976d8c331480c453590ea7ede

Observation 73ebb398-1772-4215-8b3b-86f6c1148098 · outbound

This paper cites A simple unified framework for detecting out-of-distribution samples and adversarial attacks.

Real-Time Detection and Repair of LLM Agent Failures A simple unified framework for detecting out-of-distribution samples and adversarial attacks

Reference 5

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source=pdf_text observed=2026-08-04T06:54:58.280533Z digest=sha256:a6a44f115d0a93ff71955a2ad6a4c3c00efd5ad41dc62d0747b5a51a0e44194a

Observation 8688bce4-daff-4d10-bef9-7cb412b53650 · outbound

This paper cites A baseline for detecting misclassified and out-of-distribution examples in neural networks.

Real-Time Detection and Repair of LLM Agent Failures A baseline for detecting misclassified and out-of-distribution examples in neural networks

Reference 6

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source=pdf_text observed=2026-08-04T06:54:58.352096Z digest=sha256:59a6568f7d407696a581fbec785c9365200780f70785bd0b8830d810d151ac00

Observation d5d756c6-bd9c-40b5-ba51-a11c9c29a5e0 · outbound

This paper cites Isolation forest.

Real-Time Detection and Repair of LLM Agent Failures Isolation forest

Reference 7

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source=pdf_text observed=2026-08-04T06:54:58.400309Z digest=sha256:813070e8a2bf65444365c6ea3d4c648f3329290870a48fe714b11cc0035d2079

Observation faf41244-8c29-4bb1-8434-c11fb4811ba3 · outbound

This paper cites echo state.

Real-Time Detection and Repair of LLM Agent Failures echo state

Reference 8

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source=pdf_text observed=2026-08-04T06:54:58.462731Z digest=sha256:486f2bdc3c1942e19fae3394d2624d9cb675061285b5428fe46ee8e776bc7ad3

Observation 6fef60b9-1b1e-4ea2-8634-f4d7e002b876 · outbound

This paper cites Reservoir computing approaches to recurrent neural network training.Computer Science Review, 3(3):127–149, 2009.

Real-Time Detection and Repair of LLM Agent Failures Reservoir computing approaches to recurrent neural network training.Computer Science Review, 3(3):127–149, 2009

Reference 9

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source=pdf_text observed=2026-08-04T06:54:58.494164Z digest=sha256:323bc0488bf3c9bd93efa02ae25c26d6331dc3c7cee8ee1d2a6350555486e658

Observation 9b574c79-3374-4d7b-b1d1-0698b972b466 · outbound

This paper cites Weinberger.

Real-Time Detection and Repair of LLM Agent Failures Weinberger

Reference 10

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source=pdf_text observed=2026-08-04T06:54:58.549901Z digest=sha256:6dead1526239989f2f21962c956159f9d5a9b438502f74ae1397cbd7b2f4fbcf

Observation e7f56cb9-5750-45c2-bea7-38e89a51bcb3 · outbound

This paper cites ReAct: Synergizing reasoning and acting in language models.

Real-Time Detection and Repair of LLM Agent Failures ReAct: Synergizing reasoning and acting in language models

Reference 11

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source=pdf_text observed=2026-08-04T06:54:58.623364Z digest=sha256:02015a822dfc466a55d224f4fae6c60fb76b1c7aa95a4c1516c71106884d6f0f

Observation fc11515a-2112-4277-afc1-4f3868ac4469 · outbound

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

Real-Time Detection and Repair of LLM Agent Failures AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 12

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source=pdf_text observed=2026-08-04T06:54:58.680992Z digest=sha256:418ed85f0946847632472e5313a27bb24e10bb23fa257c767a564289049b9100

Observation afdac1f3-10fe-4ced-be82-1417ec72e163 · outbound

This paper cites AgentBench: Evaluating LLMs as agents.

Real-Time Detection and Repair of LLM Agent Failures AgentBench: Evaluating LLMs as agents

Reference 13

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source=pdf_text observed=2026-08-04T06:54:58.733386Z digest=sha256:c6162813bf72dfb528372446882e34e158d44c519526514ce5089c5a49df670d

Observation d1530fa7-f8a2-4db9-b535-e164f23c1215 · outbound

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

Real-Time Detection and Repair of LLM Agent Failures Why Do Multi-Agent LLM Systems Fail?

Reference 14

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source=pdf_text observed=2026-08-04T06:54:58.783187Z digest=sha256:60cfe6ce7c8a62a739eca848b94d60af16795d22e04adee7ea542727bcfe4feb

Observation ddc7c400-5ab8-470a-b18a-c945d00cd642 · outbound

This paper cites Which Agent Causes Task Failures and When? On Automated Failure Attribution of LLM Multi-Agent Systems.

Real-Time Detection and Repair of LLM Agent Failures Which Agent Causes Task Failures and When? On Automated Failure Attribution of LLM Multi-Agent Systems

Reference 15

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source=pdf_text observed=2026-08-04T06:54:58.850261Z digest=sha256:961af5ca5196c72452f784fe23386b1337a069276b3ccd1925b49a0580899e19

Observation c698565d-c73e-437d-b442-2d013e5aebc8 · outbound

This paper cites AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems.

Real-Time Detection and Repair of LLM Agent Failures AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems

Reference 16

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source=pdf_text observed=2026-08-04T06:54:58.898072Z digest=sha256:a627ae21dab2b89691f105b121f67a8dc6a74239ae0ec5bf1b4236bf63a43324

Observation ade27ff5-89e4-4248-bff5-9c59b72de0a6 · outbound

This paper cites When Evidence is Sparse: Weakly Supervised Early Failure Alerting in Dialogs and LLM-Agent Trajectories.

Real-Time Detection and Repair of LLM Agent Failures When Evidence is Sparse: Weakly Supervised Early Failure Alerting in Dialogs and LLM-Agent Trajectories

Reference 17

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source=pdf_text observed=2026-08-04T06:54:58.997189Z digest=sha256:c38f8caf94eab351c50cd11796733da30cf8b58dd8099e9dea47c135fde9f497

Observation 7d44738f-0630-4f36-b21f-309626bc15ca · outbound

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

Real-Time Detection and Repair of LLM Agent Failures AgentSpec: Customizable Runtime Enforcement for Safe and Reliable LLM Agents

Reference 18

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source=pdf_text observed=2026-08-04T06:54:59.084112Z digest=sha256:e67ab2c5a55edc158b6b0f7b944e5239bac8657ed3b0590ca7ad74cdeca6743b

Observation 86b6f1d3-adf0-41bf-b8ca-c18627901afa · outbound

This paper cites ProbGuard: Proactive Runtime Monitoring for LLM Agent Safety via Probabilistic Prediction.

Real-Time Detection and Repair of LLM Agent Failures ProbGuard: Proactive Runtime Monitoring for LLM Agent Safety via Probabilistic Prediction

Reference 19

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source=pdf_text observed=2026-08-04T06:54:59.189094Z digest=sha256:e1023a713ccf3b07a536a2442ff60c4b09ddaebc2c614d378166970d8be25b51

Observation f80beb1f-ee05-42d0-a657-d0e74032b9c2 · outbound

This paper cites PrefixGuard: From LLM-Agent Traces to Online Failure-Warning Monitors.

Real-Time Detection and Repair of LLM Agent Failures PrefixGuard: From LLM-Agent Traces to Online Failure-Warning Monitors

Reference 20

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source=pdf_text observed=2026-08-04T06:54:59.306056Z digest=sha256:6d65ba714559eec8dede8922f8aa0591b8656b72cc67b63e7b6e2b65e699ea95

Observation 24d23cb4-5fc9-4202-9b05-9e377b927af9 · outbound

This paper cites Trajectory guard: A lightweight, sequence-aware model for real-time anomaly detection in agentic AI.arXiv preprint arXiv:2601.00516, 2026.

Real-Time Detection and Repair of LLM Agent Failures Trajectory guard: A lightweight, sequence-aware model for real-time anomaly detection in agentic AI.arXiv preprint arXiv:2601.00516, 2026

Reference 21

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source=pdf_text observed=2026-08-04T06:54:59.426206Z digest=sha256:d2442d4f2177dfe3fd59a80d86ca70aa00d80dd27ee9f85cd25b22915f04e893

Observation ca34b1f9-e2e0-49f4-a92f-0933fcb6bc11 · outbound

This paper cites AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation.

Real-Time Detection and Repair of LLM Agent Failures AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation

Reference 22

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source=pdf_text observed=2026-08-04T06:54:59.538072Z digest=sha256:cb1bab6e459ce30242928c23c814b28f4eda2bd01c76f6376e084f725ce42e7b

Observation 5cc7db64-dada-4df6-845c-56eb2488ed3c · outbound

This paper cites A Survey on LLM-as-a-Judge.

Real-Time Detection and Repair of LLM Agent Failures A Survey on LLM-as-a-Judge

Reference 23

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source=pdf_text observed=2026-08-04T06:54:59.633807Z digest=sha256:8303883f814d731501e8761be8f77c4bf12bf9255617678f747fc8cf98d9cac5

Observation 2c2187ab-0423-4007-8c50-048c2c92f1c8 · outbound

This paper cites Judging the judges: A systematic study of position bias in LLM-as-a-judge.

Real-Time Detection and Repair of LLM Agent Failures Judging the judges: A systematic study of position bias in LLM-as-a-judge

Reference 24

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source=pdf_text observed=2026-08-04T06:54:59.791427Z digest=sha256:a080345083abc160dd034a829dfa311d3b10f28a46a727acefca7d89d28ed5e3

Observation 11c8ca27-81b1-4063-8908-c355b8cba8cc · outbound

This paper cites Survey of hallucination in natural language generation.

Real-Time Detection and Repair of LLM Agent Failures Survey of hallucination in natural language generation

Reference 25

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source=pdf_text observed=2026-08-04T06:55:00.018332Z digest=sha256:664d8e05b599192cde9899e98298a02f537491664f76c5d8cf97c8f1bce64f92

Observation f10f3346-1eab-4ce1-be51-9c66bc302c64 · outbound

This paper cites LLM-based agents suffer from hallucinations: A survey of taxonomy, methods, and directions.arXiv preprint arXiv:2509.18970, 2025.

Real-Time Detection and Repair of LLM Agent Failures LLM-based agents suffer from hallucinations: A survey of taxonomy, methods, and directions.arXiv preprint arXiv:2509.18970, 2025

Reference 26

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source=pdf_text observed=2026-08-04T06:55:00.130159Z digest=sha256:7aceb51bc5c82a4ec63da08c2d9512f514812b0ce89f8190d5632558dc1db37e

Observation 5d579ccd-642e-4b5b-92ba-2fc132795706 · outbound

This paper cites an unresolved cited work.

Real-Time Detection and Repair of LLM Agent Failures Unresolved cited work

Reference 27

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source=pdf_text observed=2026-08-04T06:55:00.286127Z digest=sha256:712702bc3548b0bf9551fd9a5713d583c321f002a5278bd8a733a2f662fd4e0d

Observation e1182a1c-ad50-4c91-b182-abdcf12b099c · outbound

This paper cites Detecting hallucinations in large language models using semantic entropy.Nature, 630:625–630, 2024.

Real-Time Detection and Repair of LLM Agent Failures Detecting hallucinations in large language models using semantic entropy.Nature, 630:625–630, 2024

Reference 28

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source=pdf_text observed=2026-08-04T06:55:00.399994Z digest=sha256:cd0c73f054ee067054c5bdd34cce6161674aba34b6facb32f409c34d51c7031f

Observation 9e9b479b-4b3a-4ec2-ad97-c86dd9464e03 · outbound

This paper cites Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs.

Real-Time Detection and Repair of LLM Agent Failures Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs

Reference 29

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source=pdf_text observed=2026-08-04T06:55:00.551554Z digest=sha256:06fcf1ecae69e7abdf9fd2e180d8e8932f63d87f4e6ea82b4b6ed89752906aba

Observation cb9a404e-a308-4da1-a1ac-7ff1e3436b3e · outbound

This paper cites Detect- ing strategic deception with linear probes.

Real-Time Detection and Repair of LLM Agent Failures Detect- ing strategic deception with linear probes

Reference 30

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source=pdf_text observed=2026-08-04T06:55:00.615627Z digest=sha256:8ea42cc24e698c1f70a8d3a4ff71b34913ca501f82ed00a1e5e1c905be146fed

Observation 2224317c-955d-4bc0-a27d-5993888fa133 · outbound

This paper cites Doomed from the Start: Early Abort of LLM Agent Episodes via a Recall-Controlled Probe Cascade.

Real-Time Detection and Repair of LLM Agent Failures Doomed from the Start: Early Abort of LLM Agent Episodes via a Recall-Controlled Probe Cascade

Reference 31

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source=pdf_text observed=2026-08-04T06:55:00.672783Z digest=sha256:27adb6c381494ee8d6a27ab60ffbfb63bf391e4e6166d31d092079f1b9d004fe

Observation 8b825fc8-b5d6-4eeb-bd57-e49ab17d463c · outbound

This paper cites ATBench: A Diverse and Realistic Agent Trajectory Benchmark for Safety Evaluation and Diagnosis.

Real-Time Detection and Repair of LLM Agent Failures ATBench: A Diverse and Realistic Agent Trajectory Benchmark for Safety Evaluation and Diagnosis

Reference 32

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source=pdf_text observed=2026-08-04T06:55:00.757185Z digest=sha256:4de6a0873f1b9f5c4694b6b9bb0f5d2bbec77fefddd703ed046a57ebc17a1de9

Observation aadfbe84-6e98-4452-b339-d13825ccf344 · outbound

This paper cites an unresolved cited work.

Real-Time Detection and Repair of LLM Agent Failures Unresolved cited work

Reference 2025

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source=pdf_text observed=2026-08-04T06:54:59.906299Z digest=sha256:bef80c37c7463f031229a7b1f3023bbf7b52598c4197a2255aac9bc4aad0dd16

Pith citing papers

No inbound Pith citation observations are available.