{"id":"073b6591bed5474172e642c76cf63ce4fdb764d33eae17fdda6a329fb972892b","title":"When safeguard decisions are linked, risk assessments can mislead","argument":"Yijia Li, Maochao Xu and Peng Zhao argue that risk assessments can mislead when they overlook dependence among AI-agent safeguard decisions. Their framework jointly selects configurations and operating policies for sequential layered screening and selective verification.\n\nIn numerical experiments, the authors report that independence-based selections violated security requirements in six of eight scenarios. In an empirical study using four LLM safeguards on benchmark-derived agent actions, dependence-aware selection lowered held-out total cost by 39.6% relative to independence-based selection under the principal operating setting. The authors also provide DAPOA, an open-source software package to implement the framework.\n\nThe abstract does not establish whether these results carry over to agent actions and safeguard systems beyond those studied.","topicIds":["intelligence-and-discovery"],"domain":"science","claimType":"attributed reading","limits":"The evidence supplied is the paper's abstract; it does not provide the experiment design, benchmark details, or results needed to assess how broadly the reported findings apply. The 39.6% cost reduction is reported only for the principal operating setting and the empirical study using benchmark-derived agent actions. The abstract does not specify which safeguards or operating conditions produced the six security-requirement violations.","speaker":{"name":"Li, Yijia, Xu, Maochao, Zhao, Peng","roleAtSource":"Article author"},"source":{"title":"Dependence-Aware Risk Assessment and Optimal Design of AI-Agent Safeguard Systems","publisher":"arXiv cs.AI","format":"Article","url":"https://arxiv.org/abs/2611.00386","publishedAt":"2026-10-30","dateBasis":"Date basis not provided."},"evidence":[{"text":"Li, Xu and Zhao say existing risk assessments often overlook dependence among safeguard decisions, and propose a framework that accounts for it when designing multi-component safeguard systems.","excerpt":"existing risk assessments often focus on individual safeguard performance while overlooking dependence among safeguard decisions","url":"https://arxiv.org/abs/2611.00386","relationship":"Source-stated"},{"text":"The proposed framework jointly selects configurations and operating policies for sequential layered screening and selective verification.","excerpt":"jointly selecting configurations and operating policies for sequential layered screening and selective verification","url":"https://arxiv.org/abs/2611.00386","relationship":"Source-stated"},{"text":"The authors report that independence-based selections violated security requirements in six of eight numerical scenarios.","excerpt":"independence-based selections violating security requirements in six of eight scenarios","url":"https://arxiv.org/abs/2611.00386","relationship":"Source-stated"},{"text":"In an empirical study using four LLM safeguards on benchmark-derived agent actions, dependence-aware selection lowered held-out total cost by 39.6% relative to independence-based selection under the principal operating setting.","excerpt":"Under the principal operating setting, dependence-aware selection lowers held-out total cost by 39.6% relative to independence-based selection.","url":"https://arxiv.org/abs/2611.00386","relationship":"Source-stated"},{"text":"The authors provide DAPOA, an open-source software package for implementing their framework.","excerpt":"An accompanying open-source software package, Dependence-Aware Policy Optimization Algorithms (DAPOA), facilitates the practical implementation of the proposed framework.","url":"https://arxiv.org/abs/2611.00386","relationship":"Source-stated"}],"sourceMedia":{"status":"not_found","sourceUrl":"https://arxiv.org/abs/2611.00386","checkedAt":"2026-11-10T06:48:07.481Z","items":[],"note":"No suitable media was found by the supported page extraction."},"assumptions":[],"openQuestion":{"attribution":"Open question","text":"How well do the reported risk assessments and cost reductions carry over to agent actions and safeguard systems beyond the benchmark-derived actions studied?"},"whatWouldChangeView":{"attribution":"Change condition not recorded","text":""},"editorialComparisons":[],"live":{"title":"When safeguard decisions are linked, risk assessments can mislead","summary":"Yijia Li, Maochao Xu and Peng Zhao argue that risk assessments can mislead when they overlook dependence among AI-agent safeguard decisions. Their framework jointly selects configurations and operating policies for sequential layered screening and selective verification.\n\nIn numerical experiments, the authors report that independence-based selections violated security requirements in six of eight scenarios. In an empirical study using four LLM safeguards on benchmark-derived agent actions, dependence-aware selection lowered held-out total cost by 39.6% relative to independence-based selection under the principal operating setting. The authors also provide DAPOA, an open-source software package to implement the framework.\n\nThe abstract does not establish whether these results carry over to agent actions and safeguard systems beyond those studied.","question":"How well do the reported risk assessments and cost reductions carry over to agent actions and safeguard systems beyond the benchmark-derived actions studied?","claims":[{"text":"Li, Xu and Zhao say existing risk assessments often overlook dependence among safeguard decisions, and propose a framework that accounts for it when designing multi-component safeguard systems.","excerpt":"existing risk assessments often focus on individual safeguard performance while overlooking dependence among safeguard decisions","support":"source-stated"},{"text":"The proposed framework jointly selects configurations and operating policies for sequential layered screening and selective verification.","excerpt":"jointly selecting configurations and operating policies for sequential layered screening and selective verification","support":"source-stated"},{"text":"The authors report that independence-based selections violated security requirements in six of eight numerical scenarios.","excerpt":"independence-based selections violating security requirements in six of eight scenarios","support":"source-stated"},{"text":"In an empirical study using four LLM safeguards on benchmark-derived agent actions, dependence-aware selection lowered held-out total cost by 39.6% relative to independence-based selection under the principal operating setting.","excerpt":"Under the principal operating setting, dependence-aware selection lowers held-out total cost by 39.6% relative to independence-based selection.","support":"source-stated"},{"text":"The authors provide DAPOA, an open-source software package for implementing their framework.","excerpt":"An accompanying open-source software package, Dependence-Aware Policy Optimization Algorithms (DAPOA), facilitates the practical implementation of the proposed framework.","support":"source-stated"}],"limitations":["The evidence supplied is the paper's abstract; it does not provide the experiment design, benchmark details, or results needed to assess how broadly the reported findings apply.","The 39.6% cost reduction is reported only for the principal operating setting and the empirical study using benchmark-derived agent actions.","The abstract does not specify which safeguards or operating conditions produced the six security-requirement violations."],"mediaId":"acb47bba80d5017e77fcb8da72e320a1ba7993d30172d3a38e4992044bc0a941","correctionReason":null,"id":"073b6591bed5474172e642c76cf63ce4fdb764d33eae17fdda6a329fb972892b","publicationId":"eda59dfe-9dc6-4ae0-8273-3a1dd1a2dc15","version":1,"sourceUrl":"https://arxiv.org/abs/2611.00386","sourceTitle":"Dependence-Aware Risk Assessment and Optimal Design of AI-Agent Safeguard Systems","publisher":"arXiv cs.AI","publishedAt":null,"originalPublished":{"value":"2026-10-30","precision":"day","basis":"publisher_citation_date"},"firstObservedAt":"2026-11-03T08:51:36.950Z","createdAt":"2026-11-10T04:40:22.405Z","historical":true,"entityIds":["arxiv"],"topicIds":["intelligence-and-discovery"],"media":[{"id":"acb47bba80d5017e77fcb8da72e320a1ba7993d30172d3a38e4992044bc0a941","kind":"article","url":"https://arxiv.org/abs/2611.00386","sourceUrl":"https://arxiv.org/abs/2611.00386","label":"Read original","provenance":"source_link","verification":{"status":"verified","checkedAt":"2026-11-04T05:00:48.419Z","method":"acquired_source","contentType":"text/html"},"recommendationReason":"Recommended by Jev for understanding this source; checked by Luna."}],"sourceMedia":{"status":"not_found","sourceUrl":"https://arxiv.org/abs/2611.00386","checkedAt":"2026-11-10T06:48:07.481Z","items":[],"note":"No suitable media was found by the supported page extraction."},"editorialDecision":{"outcome":"accept","reasonCodes":["material_development"],"rubricVersion":"stream-admission-v5","mediaId":"acb47bba80d5017e77fcb8da72e320a1ba7993d30172d3a38e4992044bc0a941","confidence":0.82,"provider":"typesafe","model":"jev-1.13.0","inputHash":"8af0bee78475ad8482ad004fd637ab4026e1e1a0b209678400a54b9523250ffa","decidedAt":"2026-11-04T05:00:49.478Z"},"provenance":{"textHash":"77b59331da274c24456b65ddd7606f5c6bdbef75405861c702b3fe1b30d8576f","observationId":"0901c03638405a38ee9d6b12676e26e547107c22f644bfb5327cb3a41c9fcd09","retrievedAt":"2026-11-04T05:00:48.329Z","kind":"publisher-page","preparer":{"model":"gpt-6-luna","runId":"9a862a80-aff5-486a-83a5-6cc754b370b4"},"reviewer":{"model":"gpt-6-luna","runId":"b73d28d5-0fbb-48e9-86c3-ef37c1337cf6"}},"audit":{"status":"uncertain","reviewedAt":"2026-11-10T04:40:22.405Z","model":"anthropic/claude-opus-5.5"},"sourceAttribution":{"authors":[{"name":"Li, Yijia","url":null,"kind":"unknown"},{"name":"Xu, Maochao","url":null,"kind":"unknown"},{"name":"Zhao, Peng","url":null,"kind":"unknown"}],"authorRole":"article-author","hosts":[],"status":"stated","authorRoster":{"truncated":false,"omitted":0,"assertionGroupsOmitted":0},"participation":[{"actor":{"name":"Li, Yijia","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Li, Yijia","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2611.00386","locator":"head/meta[name=author|citation_author]"},"assertionId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6:participation:0","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-10T06:48:07.481Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6","sourceUrl":"https://arxiv.org/abs/2611.00386","contentSha256":"2e3ede9a4f4d8e649b2402314fb5867a1d84daf862df5770854f06bcf0b3e8e4","textHash":"77b59331da274c24456b65ddd7606f5c6bdbef75405861c702b3fe1b30d8576f","observedAt":"2026-11-10T06:48:07.481Z"}},{"actor":{"name":"Xu, Maochao","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Xu, Maochao","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2611.00386","locator":"head/meta[name=author|citation_author]"},"assertionId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6:participation:1","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-10T06:48:07.481Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6","sourceUrl":"https://arxiv.org/abs/2611.00386","contentSha256":"2e3ede9a4f4d8e649b2402314fb5867a1d84daf862df5770854f06bcf0b3e8e4","textHash":"77b59331da274c24456b65ddd7606f5c6bdbef75405861c702b3fe1b30d8576f","observedAt":"2026-11-10T06:48:07.481Z"}},{"actor":{"name":"Zhao, Peng","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Zhao, Peng","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2611.00386","locator":"head/meta[name=author|citation_author]"},"assertionId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6:participation:2","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-10T06:48:07.481Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6","sourceUrl":"https://arxiv.org/abs/2611.00386","contentSha256":"2e3ede9a4f4d8e649b2402314fb5867a1d84daf862df5770854f06bcf0b3e8e4","textHash":"77b59331da274c24456b65ddd7606f5c6bdbef75405861c702b3fe1b30d8576f","observedAt":"2026-11-10T06:48:07.481Z"}}],"participationCoverage":{"total":3,"returned":3,"complete":true,"fullAssertions":"source-metadata-endpoint"},"distribution":null,"publisher":null,"sourceUrl":"https://arxiv.org/abs/2611.00386","snapshotId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6","contentSha256":"2e3ede9a4f4d8e649b2402314fb5867a1d84daf862df5770854f06bcf0b3e8e4","textHash":"77b59331da274c24456b65ddd7606f5c6bdbef75405861c702b3fe1b30d8576f","observedAt":"2026-11-10T06:48:07.481Z","basis":"publisher-page-metadata","sourceLinks":41,"linksTruncated":false,"metadataUrl":"/api/pipeline/stream/073b6591bed5474172e642c76cf63ce4fdb764d33eae17fdda6a329fb972892b/source"}},"canonicalUrl":"https://escapemeridian.com/readings/when-safeguard-decisions-are-linked-risk-assessments-can-mislead-073b6591","formats":{"html":"/readings/when-safeguard-decisions-are-linked-risk-assessments-can-mislead-073b6591","markdown":"/readings/when-safeguard-decisions-are-linked-risk-assessments-can-mislead-073b6591.md","json":"/readings/when-safeguard-decisions-are-linked-risk-assessments-can-mislead-073b6591.json"},"attribution":"Headline and summary by Escape Meridian, prepared by Luna from the attributed source. A source check is not independent confirmation of the source’s claims.","maintainedGuideLinks":[],"readerContext":{"version":"reader-context-v1","attribution":"Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.","terms":[{"id":"term-ai-agent","name":"AI agent","explanation":"An AI system that chooses and carries out actions toward a goal, often using software tools.","referenceUrl":"https://www.ibm.com/think/topics/ai-agents"},{"id":"term-llm","name":"Large language model","explanation":"A language model with many learned numerical settings, used to process and generate language.","referenceUrl":"https://developers.google.com/machine-learning/glossary#large-language-model"},{"id":"term-benchmark","name":"Benchmark","explanation":"A defined set of tests used to compare systems. Results depend on the tasks and measures selected.","referenceUrl":"https://arxiv.org/abs/2211.09110"}],"entities":[{"id":"arxiv","name":"arXiv","kind":"organization","context":"arXiv is a research manuscript repository where authors share papers that may not yet have been peer reviewed.","referenceUrls":["https://arxiv.org/","https://info.arxiv.org/help/api/index.html"],"path":"/entities/arxiv","json":"/entities/arxiv.json","markdown":"/entities/arxiv.md"}]},"researchQuestions":[],"withdrawn":false,"references":{"schemaVersion":1,"target":{"type":"reading","id":"073b6591bed5474172e642c76cf63ce4fdb764d33eae17fdda6a329fb972892b","revision":"eda59dfe-9dc6-4ae0-8273-3a1dd1a2dc15","revisionKind":"publication-id","title":"When safeguard decisions are linked, risk assessments can mislead","url":"https://escapemeridian.com/readings/when-safeguard-decisions-are-linked-risk-assessments-can-mislead-073b6591"},"source":{"type":"source","id":"https://arxiv.org/abs/2611.00386","revision":"77b59331da274c24456b65ddd7606f5c6bdbef75405861c702b3fe1b30d8576f","revisionKind":"sha256-source-text","title":"Dependence-Aware Risk Assessment and Optimal Design of AI-Agent Safeguard Systems","url":"https://arxiv.org/abs/2611.00386"},"status":"available","items":[],"next":null,"scope":"Explicit citations in public readings and public file attachments to this reading. Shared topics are not citations. Other artifact types need an explicit reference adapter."},"revisions":[{"id":"073b6591bed5474172e642c76cf63ce4fdb764d33eae17fdda6a329fb972892b","title":"When safeguard decisions are linked, risk assessments can mislead","argument":"Yijia Li, Maochao Xu and Peng Zhao argue that risk assessments can mislead when they overlook dependence among AI-agent safeguard decisions. Their framework jointly selects configurations and operating policies for sequential layered screening and selective verification.\n\nIn numerical experiments, the authors report that independence-based selections violated security requirements in six of eight scenarios. In an empirical study using four LLM safeguards on benchmark-derived agent actions, dependence-aware selection lowered held-out total cost by 39.6% relative to independence-based selection under the principal operating setting. The authors also provide DAPOA, an open-source software package to implement the framework.\n\nThe abstract does not establish whether these results carry over to agent actions and safeguard systems beyond those studied.","topicIds":["intelligence-and-discovery"],"domain":"science","claimType":"attributed reading","limits":"The evidence supplied is the paper's abstract; it does not provide the experiment design, benchmark details, or results needed to assess how broadly the reported findings apply. The 39.6% cost reduction is reported only for the principal operating setting and the empirical study using benchmark-derived agent actions. The abstract does not specify which safeguards or operating conditions produced the six security-requirement violations.","speaker":{"name":"Li, Yijia, Xu, Maochao, Zhao, Peng","roleAtSource":"Article author"},"source":{"title":"Dependence-Aware Risk Assessment and Optimal Design of AI-Agent Safeguard Systems","publisher":"arXiv cs.AI","format":"Article","url":"https://arxiv.org/abs/2611.00386","publishedAt":"2026-10-30","dateBasis":"Date basis not provided."},"evidence":[{"text":"Li, Xu and Zhao say existing risk assessments often overlook dependence among safeguard decisions, and propose a framework that accounts for it when designing multi-component safeguard systems.","excerpt":"existing risk assessments often focus on individual safeguard performance while overlooking dependence among safeguard decisions","url":"https://arxiv.org/abs/2611.00386","relationship":"Source-stated"},{"text":"The proposed framework jointly selects configurations and operating policies for sequential layered screening and selective verification.","excerpt":"jointly selecting configurations and operating policies for sequential layered screening and selective verification","url":"https://arxiv.org/abs/2611.00386","relationship":"Source-stated"},{"text":"The authors report that independence-based selections violated security requirements in six of eight numerical scenarios.","excerpt":"independence-based selections violating security requirements in six of eight scenarios","url":"https://arxiv.org/abs/2611.00386","relationship":"Source-stated"},{"text":"In an empirical study using four LLM safeguards on benchmark-derived agent actions, dependence-aware selection lowered held-out total cost by 39.6% relative to independence-based selection under the principal operating setting.","excerpt":"Under the principal operating setting, dependence-aware selection lowers held-out total cost by 39.6% relative to independence-based selection.","url":"https://arxiv.org/abs/2611.00386","relationship":"Source-stated"},{"text":"The authors provide DAPOA, an open-source software package for implementing their framework.","excerpt":"An accompanying open-source software package, Dependence-Aware Policy Optimization Algorithms (DAPOA), facilitates the practical implementation of the proposed framework.","url":"https://arxiv.org/abs/2611.00386","relationship":"Source-stated"}],"sourceMedia":{"status":"not_found","sourceUrl":"https://arxiv.org/abs/2611.00386","checkedAt":"2026-11-10T06:48:07.481Z","items":[],"note":"No suitable media was found by the supported page extraction."},"assumptions":[],"openQuestion":{"attribution":"Open question","text":"How well do the reported risk assessments and cost reductions carry over to agent actions and safeguard systems beyond the benchmark-derived actions studied?"},"whatWouldChangeView":{"attribution":"Change condition not recorded","text":""},"editorialComparisons":[],"live":{"title":"When safeguard decisions are linked, risk assessments can mislead","summary":"Yijia Li, Maochao Xu and Peng Zhao argue that risk assessments can mislead when they overlook dependence among AI-agent safeguard decisions. Their framework jointly selects configurations and operating policies for sequential layered screening and selective verification.\n\nIn numerical experiments, the authors report that independence-based selections violated security requirements in six of eight scenarios. In an empirical study using four LLM safeguards on benchmark-derived agent actions, dependence-aware selection lowered held-out total cost by 39.6% relative to independence-based selection under the principal operating setting. The authors also provide DAPOA, an open-source software package to implement the framework.\n\nThe abstract does not establish whether these results carry over to agent actions and safeguard systems beyond those studied.","question":"How well do the reported risk assessments and cost reductions carry over to agent actions and safeguard systems beyond the benchmark-derived actions studied?","claims":[{"text":"Li, Xu and Zhao say existing risk assessments often overlook dependence among safeguard decisions, and propose a framework that accounts for it when designing multi-component safeguard systems.","excerpt":"existing risk assessments often focus on individual safeguard performance while overlooking dependence among safeguard decisions","support":"source-stated"},{"text":"The proposed framework jointly selects configurations and operating policies for sequential layered screening and selective verification.","excerpt":"jointly selecting configurations and operating policies for sequential layered screening and selective verification","support":"source-stated"},{"text":"The authors report that independence-based selections violated security requirements in six of eight numerical scenarios.","excerpt":"independence-based selections violating security requirements in six of eight scenarios","support":"source-stated"},{"text":"In an empirical study using four LLM safeguards on benchmark-derived agent actions, dependence-aware selection lowered held-out total cost by 39.6% relative to independence-based selection under the principal operating setting.","excerpt":"Under the principal operating setting, dependence-aware selection lowers held-out total cost by 39.6% relative to independence-based selection.","support":"source-stated"},{"text":"The authors provide DAPOA, an open-source software package for implementing their framework.","excerpt":"An accompanying open-source software package, Dependence-Aware Policy Optimization Algorithms (DAPOA), facilitates the practical implementation of the proposed framework.","support":"source-stated"}],"limitations":["The evidence supplied is the paper's abstract; it does not provide the experiment design, benchmark details, or results needed to assess how broadly the reported findings apply.","The 39.6% cost reduction is reported only for the principal operating setting and the empirical study using benchmark-derived agent actions.","The abstract does not specify which safeguards or operating conditions produced the six security-requirement violations."],"mediaId":"acb47bba80d5017e77fcb8da72e320a1ba7993d30172d3a38e4992044bc0a941","correctionReason":null,"id":"073b6591bed5474172e642c76cf63ce4fdb764d33eae17fdda6a329fb972892b","publicationId":"eda59dfe-9dc6-4ae0-8273-3a1dd1a2dc15","version":1,"sourceUrl":"https://arxiv.org/abs/2611.00386","sourceTitle":"Dependence-Aware Risk Assessment and Optimal Design of AI-Agent Safeguard Systems","publisher":"arXiv cs.AI","publishedAt":null,"originalPublished":{"value":"2026-10-30","precision":"day","basis":"publisher_citation_date"},"firstObservedAt":"2026-11-03T08:51:36.950Z","createdAt":"2026-11-10T04:40:22.405Z","historical":true,"entityIds":["arxiv"],"topicIds":["intelligence-and-discovery"],"media":[{"id":"acb47bba80d5017e77fcb8da72e320a1ba7993d30172d3a38e4992044bc0a941","kind":"article","url":"https://arxiv.org/abs/2611.00386","sourceUrl":"https://arxiv.org/abs/2611.00386","label":"Read original","provenance":"source_link","verification":{"status":"verified","checkedAt":"2026-11-04T05:00:48.419Z","method":"acquired_source","contentType":"text/html"},"recommendationReason":"Recommended by Jev for understanding this source; checked by Luna."}],"sourceMedia":{"status":"not_found","sourceUrl":"https://arxiv.org/abs/2611.00386","checkedAt":"2026-11-10T06:48:07.481Z","items":[],"note":"No suitable media was found by the supported page extraction."},"editorialDecision":{"outcome":"accept","reasonCodes":["material_development"],"rubricVersion":"stream-admission-v5","mediaId":"acb47bba80d5017e77fcb8da72e320a1ba7993d30172d3a38e4992044bc0a941","confidence":0.82,"provider":"typesafe","model":"jev-1.13.0","inputHash":"8af0bee78475ad8482ad004fd637ab4026e1e1a0b209678400a54b9523250ffa","decidedAt":"2026-11-04T05:00:49.478Z"},"provenance":{"textHash":"77b59331da274c24456b65ddd7606f5c6bdbef75405861c702b3fe1b30d8576f","observationId":"0901c03638405a38ee9d6b12676e26e547107c22f644bfb5327cb3a41c9fcd09","retrievedAt":"2026-11-04T05:00:48.329Z","kind":"publisher-page","preparer":{"model":"gpt-6-luna","runId":"9a862a80-aff5-486a-83a5-6cc754b370b4"},"reviewer":{"model":"gpt-6-luna","runId":"b73d28d5-0fbb-48e9-86c3-ef37c1337cf6"}},"audit":{"status":"uncertain","reviewedAt":"2026-11-10T04:40:22.405Z","model":"anthropic/claude-opus-5.5"},"sourceAttribution":{"authors":[{"name":"Li, Yijia","url":null,"kind":"unknown"},{"name":"Xu, Maochao","url":null,"kind":"unknown"},{"name":"Zhao, Peng","url":null,"kind":"unknown"}],"authorRole":"article-author","hosts":[],"status":"stated","authorRoster":{"truncated":false,"omitted":0,"assertionGroupsOmitted":0},"participation":[{"actor":{"name":"Li, Yijia","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Li, Yijia","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2611.00386","locator":"head/meta[name=author|citation_author]"},"assertionId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6:participation:0","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-10T06:48:07.481Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6","sourceUrl":"https://arxiv.org/abs/2611.00386","contentSha256":"2e3ede9a4f4d8e649b2402314fb5867a1d84daf862df5770854f06bcf0b3e8e4","textHash":"77b59331da274c24456b65ddd7606f5c6bdbef75405861c702b3fe1b30d8576f","observedAt":"2026-11-10T06:48:07.481Z"}},{"actor":{"name":"Xu, Maochao","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Xu, Maochao","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2611.00386","locator":"head/meta[name=author|citation_author]"},"assertionId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6:participation:1","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-10T06:48:07.481Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6","sourceUrl":"https://arxiv.org/abs/2611.00386","contentSha256":"2e3ede9a4f4d8e649b2402314fb5867a1d84daf862df5770854f06bcf0b3e8e4","textHash":"77b59331da274c24456b65ddd7606f5c6bdbef75405861c702b3fe1b30d8576f","observedAt":"2026-11-10T06:48:07.481Z"}},{"actor":{"name":"Zhao, Peng","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Zhao, Peng","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2611.00386","locator":"head/meta[name=author|citation_author]"},"assertionId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6:participation:2","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-10T06:48:07.481Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6","sourceUrl":"https://arxiv.org/abs/2611.00386","contentSha256":"2e3ede9a4f4d8e649b2402314fb5867a1d84daf862df5770854f06bcf0b3e8e4","textHash":"77b59331da274c24456b65ddd7606f5c6bdbef75405861c702b3fe1b30d8576f","observedAt":"2026-11-10T06:48:07.481Z"}}],"participationCoverage":{"total":3,"returned":3,"complete":true,"fullAssertions":"source-metadata-endpoint"},"distribution":null,"publisher":null,"sourceUrl":"https://arxiv.org/abs/2611.00386","snapshotId":"dcc08a3f4ef0d1776a71c850e8805392176d647f5290c73ba658ee7a31d3d7a6","contentSha256":"2e3ede9a4f4d8e649b2402314fb5867a1d84daf862df5770854f06bcf0b3e8e4","textHash":"77b59331da274c24456b65ddd7606f5c6bdbef75405861c702b3fe1b30d8576f","observedAt":"2026-11-10T06:48:07.481Z","basis":"publisher-page-metadata","sourceLinks":41,"linksTruncated":false,"metadataUrl":"/api/pipeline/stream/073b6591bed5474172e642c76cf63ce4fdb764d33eae17fdda6a329fb972892b/source"}}}],"audits":[{"publicationId":"eda59dfe-9dc6-4ae0-8273-3a1dd1a2dc15","verdict":"uncertain","findings":[{"dimension":"attribution","status":"pass","explanation":"The reading correctly attributes the paper and its claims to Yijia Li, Maochao Xu and Peng Zhao. It keeps the results framed as what the authors report, not as established fact.","excerpt":"Authors:Yijia Li, Maochao Xu, Peng Zhao"},{"dimension":"summary","status":"uncertain","explanation":"The reading is faithful, but its central idea stays in jargon. It never says in plain language what a safeguard does: the source says safeguards prevent unauthorized actions while preserving legitimate service. It also never explains what dependence among safeguard decisions means, for example that safeguards may tend to err on the same cases, so stacked checks protect less than assumed. Terms such as layered screening, selective verification, independence-based selection, held-out total cost and principal operating setting go unexplained. Smallest repair: add one plain sentence each on the safeguards' purpose and on dependence, and add tooltips for the other terms.","excerpt":"Large language model (LLM) agents increasingly rely on safeguards to prevent unauthorized actions while preserving legitimate service."},{"dimension":"date","status":"pass","explanation":"The displayed original publication date of 2026-10-30 matches the source's first submission (v1). It is not taken from the later feed date.","excerpt":"[Submitted on 30 Oct 2026]"},{"dimension":"support","status":"pass","explanation":"Each claim matches the abstract verbatim in substance, including the six-of-eight scenarios result, the 39.6% figure with its condition, and DAPOA. The limitations and the question about generalization are appropriately conditional and do not overstate the results.","excerpt":"Under the principal operating setting, dependence-aware selection lowers held-out total cost by 39.6% relative to independence-based selection."},{"dimension":"media","status":"pass","explanation":"The selected media is the verified direct arXiv abstract page for this paper, which is the most direct access to the source.","excerpt":null}],"createdAt":"2026-11-10T04:40:22.405Z","model":"anthropic/claude-opus-5.5"}],"correctionUrl":"https://escapemeridian.com/corrections/"}