{"id":"517f025428a8e9a7f1eadab615def84b13829e87b93352695ff671852866d0b2","title":"Daniel Rupawalla presents Bank-World, a benchmark for banking workflows","argument":"Daniel Rupawalla presents Bank-World as a benchmark for testing whether agents can complete banking workflows in two simulated institutions. The paper argues that getting a calculation right is not enough: agents must reconcile records, obtain permission, execute transactions, and keep instructions and status reports consistent as circumstances change.\n\nBank-World tests single-turn assignments and multi-turn interactions with simulated employees who provide information, approve actions, and revise instructions. Grading combines executable checks of recorded actions and state with model judgments about task requirements, including whether valid alternatives count. Across 1,600 attempts by four models, the authors report cases where correct decisions did not become completed work: agents charged fees twice, split a correct total incorrectly among recipients, or paid while approval was pending. The reported strengths differ by task: Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently.\n\nThe paper’s practical contribution is an evaluation that connects task evidence, agent decisions, and simulated consequences through task-level results and worked examples.","topicIds":["intelligence-and-discovery"],"domain":"science","claimType":"attributed reading","limits":"The evidence is an arXiv abstract; it does not provide the task-level results or worked examples described in the paper. The benchmark uses simulated institutions, so the abstract does not establish how its results correspond to performance in real banking workflows. The authors say they retain the task environments, executable graders, and full trajectories privately to reduce contamination and preserve the benchmark for future evaluations.","speaker":{"name":"Rupawalla, Daniel","roleAtSource":"Article author"},"source":{"title":"Bank-World: A Benchmark for Evaluating Agents on Banking Workflows","publisher":"arXiv cs.AI","format":"Article","url":"https://arxiv.org/abs/2610.39733","publishedAt":"2026-10-29","dateBasis":"Date basis not provided."},"evidence":[{"text":"Rupawalla presents Bank-World as a benchmark of 50 banking tasks across two simulated institutions.","excerpt":"Bank-World is a benchmark of 50 banking tasks across two simulated institutions.","url":"https://arxiv.org/abs/2610.39733","relationship":"Source-stated"},{"text":"The benchmark evaluates workflow steps beyond calculation, including record reconciliation, permission, transactions, and consistent instructions and status reports.","excerpt":"agents must reconcile records, obtain permission, execute transactions, and keep instructions and status reports consistent as circumstances change.","url":"https://arxiv.org/abs/2610.39733","relationship":"Source-stated"},{"text":"Its grading combines executable checks with model judgments, including judgments about valid alternative solutions.","excerpt":"Grading combines executable checks of recorded actions and state with model judgments of task requirements, including whether valid alternative solutions satisfy them.","url":"https://arxiv.org/abs/2610.39733","relationship":"Source-stated"},{"text":"Across 1,600 attempts by four models, the authors report failures in which correct decisions did not become completed work.","excerpt":"Across 1,600 attempts by four models, we find that correct decisions often fail to become completed work.","url":"https://arxiv.org/abs/2610.39733","relationship":"Source-stated"},{"text":"The authors report different strengths across models: Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently.","excerpt":"Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently.","url":"https://arxiv.org/abs/2610.39733","relationship":"Source-stated"},{"text":"The authors say the benchmark makes model differences inspectable through task-level results and worked examples connecting evidence, decisions, and simulated consequences.","excerpt":"task-level results and worked examples connecting source evidence, agent decisions, and simulated consequences.","url":"https://arxiv.org/abs/2610.39733","relationship":"Source-stated"}],"sourceMedia":{"status":"not_found","sourceUrl":"https://arxiv.org/abs/2610.39733","checkedAt":"2026-11-12T05:58:09.118Z","items":[],"note":"No suitable media was found by the supported page extraction."},"assumptions":[],"openQuestion":{"attribution":"Open question","text":"How well would the reported task-level differences predict agents’ performance in real banking workflows, beyond these simulated institutions?"},"whatWouldChangeView":{"attribution":"Change condition not recorded","text":""},"editorialComparisons":[],"live":{"title":"Daniel Rupawalla presents Bank-World, a benchmark for banking workflows","summary":"Daniel Rupawalla presents Bank-World as a benchmark for testing whether agents can complete banking workflows in two simulated institutions. The paper argues that getting a calculation right is not enough: agents must reconcile records, obtain permission, execute transactions, and keep instructions and status reports consistent as circumstances change.\n\nBank-World tests single-turn assignments and multi-turn interactions with simulated employees who provide information, approve actions, and revise instructions. Grading combines executable checks of recorded actions and state with model judgments about task requirements, including whether valid alternatives count. Across 1,600 attempts by four models, the authors report cases where correct decisions did not become completed work: agents charged fees twice, split a correct total incorrectly among recipients, or paid while approval was pending. The reported strengths differ by task: Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently.\n\nThe paper’s practical contribution is an evaluation that connects task evidence, agent decisions, and simulated consequences through task-level results and worked examples.","question":"How well would the reported task-level differences predict agents’ performance in real banking workflows, beyond these simulated institutions?","claims":[{"text":"Rupawalla presents Bank-World as a benchmark of 50 banking tasks across two simulated institutions.","excerpt":"Bank-World is a benchmark of 50 banking tasks across two simulated institutions.","support":"source-stated"},{"text":"The benchmark evaluates workflow steps beyond calculation, including record reconciliation, permission, transactions, and consistent instructions and status reports.","excerpt":"agents must reconcile records, obtain permission, execute transactions, and keep instructions and status reports consistent as circumstances change.","support":"source-stated"},{"text":"Its grading combines executable checks with model judgments, including judgments about valid alternative solutions.","excerpt":"Grading combines executable checks of recorded actions and state with model judgments of task requirements, including whether valid alternative solutions satisfy them.","support":"source-stated"},{"text":"Across 1,600 attempts by four models, the authors report failures in which correct decisions did not become completed work.","excerpt":"Across 1,600 attempts by four models, we find that correct decisions often fail to become completed work.","support":"source-stated"},{"text":"The authors report different strengths across models: Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently.","excerpt":"Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently.","support":"source-stated"},{"text":"The authors say the benchmark makes model differences inspectable through task-level results and worked examples connecting evidence, decisions, and simulated consequences.","excerpt":"task-level results and worked examples connecting source evidence, agent decisions, and simulated consequences.","support":"source-stated"}],"limitations":["The evidence is an arXiv abstract; it does not provide the task-level results or worked examples described in the paper.","The benchmark uses simulated institutions, so the abstract does not establish how its results correspond to performance in real banking workflows.","The authors say they retain the task environments, executable graders, and full trajectories privately to reduce contamination and preserve the benchmark for future evaluations."],"mediaId":"f9665e77a058fd7ace3304eab7951bb8e78feb9dd954757425b07ebf404d35b0","correctionReason":null,"id":"517f025428a8e9a7f1eadab615def84b13829e87b93352695ff671852866d0b2","publicationId":"0a6a8906-7259-48f0-8854-19340372aaf1","version":1,"sourceUrl":"https://arxiv.org/abs/2610.39733","sourceTitle":"Bank-World: A Benchmark for Evaluating Agents on Banking Workflows","publisher":"arXiv cs.AI","publishedAt":null,"originalPublished":{"value":"2026-10-29","precision":"day","basis":"publisher_citation_date"},"firstObservedAt":"2026-10-30T06:43:03.996Z","createdAt":"2026-11-11T12:54:59.606Z","historical":true,"entityIds":["arxiv"],"topicIds":["intelligence-and-discovery"],"media":[{"id":"f9665e77a058fd7ace3304eab7951bb8e78feb9dd954757425b07ebf404d35b0","kind":"article","url":"https://arxiv.org/abs/2610.39733","sourceUrl":"https://arxiv.org/abs/2610.39733","label":"Read original","provenance":"source_link","verification":{"status":"verified","checkedAt":"2026-10-31T06:31:17.473Z","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/2610.39733","checkedAt":"2026-11-12T05:58:09.118Z","items":[],"note":"No suitable media was found by the supported page extraction."},"editorialDecision":{"outcome":"accept","reasonCodes":["material_development"],"rubricVersion":"stream-admission-v5","mediaId":"f9665e77a058fd7ace3304eab7951bb8e78feb9dd954757425b07ebf404d35b0","confidence":0.8200000000000001,"provider":"typesafe","model":"jev-1.13.0","inputHash":"0799b50c56de77767ad0967ffdf3e862341474b54a1e2309f1c022d5dc8a6d50","decidedAt":"2026-10-31T06:31:19.143Z"},"provenance":{"textHash":"f0983f6d8b89353e05493386c541f148b0ff3e0d9c8352771c0276afe3404d5f","observationId":"ecd7ba3eaf27ca01a13acaed4d384fe57d8f666716a17fda63b19eb47c43f339","retrievedAt":"2026-10-31T06:31:17.187Z","kind":"publisher-page","preparer":{"model":"gpt-6-luna","runId":"d4a3eaa8-c59b-4ba4-8392-9b42a53f3cd3"},"reviewer":{"model":"gpt-6-luna","runId":"1802dfcd-b0ee-43e9-8e5a-183d40b446fe"}},"audit":{"status":"uncertain","reviewedAt":"2026-11-11T12:54:59.606Z","model":"anthropic/claude-opus-5.5"},"sourceAttribution":{"authors":[{"name":"Rupawalla, Daniel","url":null,"kind":"unknown"}],"authorRole":"article-author","hosts":[],"status":"stated","authorRoster":{"truncated":false,"omitted":0,"assertionGroupsOmitted":0},"participation":[{"actor":{"name":"Rupawalla, Daniel","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Rupawalla, Daniel","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2610.39733","locator":"head/meta[name=author|citation_author]"},"assertionId":"32b91507f283d8f91003ed28d244190ce663c583f67e9d2b4244f1b3036af45c:participation:0","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-12T05:58:09.118Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"32b91507f283d8f91003ed28d244190ce663c583f67e9d2b4244f1b3036af45c","sourceUrl":"https://arxiv.org/abs/2610.39733","contentSha256":"c9ca6cfa663025ea62aadd1ec891b1a88869d409284a87ad63c850459082896e","textHash":"f0983f6d8b89353e05493386c541f148b0ff3e0d9c8352771c0276afe3404d5f","observedAt":"2026-11-12T05:58:09.118Z"}}],"participationCoverage":{"total":1,"returned":1,"complete":true,"fullAssertions":"source-metadata-endpoint"},"distribution":null,"publisher":null,"sourceUrl":"https://arxiv.org/abs/2610.39733","snapshotId":"32b91507f283d8f91003ed28d244190ce663c583f67e9d2b4244f1b3036af45c","contentSha256":"c9ca6cfa663025ea62aadd1ec891b1a88869d409284a87ad63c850459082896e","textHash":"f0983f6d8b89353e05493386c541f148b0ff3e0d9c8352771c0276afe3404d5f","observedAt":"2026-11-12T05:58:09.118Z","basis":"publisher-page-metadata","sourceLinks":43,"linksTruncated":false,"metadataUrl":"/api/pipeline/stream/517f025428a8e9a7f1eadab615def84b13829e87b93352695ff671852866d0b2/source"}},"canonicalUrl":"https://escapemeridian.com/readings/daniel-rupawalla-presents-bank-world-a-benchmark-for-banking-517f0254","formats":{"html":"/readings/daniel-rupawalla-presents-bank-world-a-benchmark-for-banking-517f0254","markdown":"/readings/daniel-rupawalla-presents-bank-world-a-benchmark-for-banking-517f0254.md","json":"/readings/daniel-rupawalla-presents-bank-world-a-benchmark-for-banking-517f0254.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-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"},{"id":"grok","name":"Grok","kind":"model","context":"Grok is a family of AI models from xAI, with capability claims and evaluations published by its developer.","referenceUrls":["https://x.ai/grok","https://x.ai/news/grok-4-7"],"path":"/entities/grok","json":"/entities/grok.json","markdown":"/entities/grok.md"}]},"researchQuestions":[],"withdrawn":false,"references":{"schemaVersion":1,"target":{"type":"reading","id":"517f025428a8e9a7f1eadab615def84b13829e87b93352695ff671852866d0b2","revision":"0a6a8906-7259-48f0-8854-19340372aaf1","revisionKind":"publication-id","title":"Daniel Rupawalla presents Bank-World, a benchmark for banking workflows","url":"https://escapemeridian.com/readings/daniel-rupawalla-presents-bank-world-a-benchmark-for-banking-517f0254"},"source":{"type":"source","id":"https://arxiv.org/abs/2610.39733","revision":"f0983f6d8b89353e05493386c541f148b0ff3e0d9c8352771c0276afe3404d5f","revisionKind":"sha256-source-text","title":"Bank-World: A Benchmark for Evaluating Agents on Banking Workflows","url":"https://arxiv.org/abs/2610.39733"},"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":"517f025428a8e9a7f1eadab615def84b13829e87b93352695ff671852866d0b2","title":"Daniel Rupawalla presents Bank-World, a benchmark for banking workflows","argument":"Daniel Rupawalla presents Bank-World as a benchmark for testing whether agents can complete banking workflows in two simulated institutions. The paper argues that getting a calculation right is not enough: agents must reconcile records, obtain permission, execute transactions, and keep instructions and status reports consistent as circumstances change.\n\nBank-World tests single-turn assignments and multi-turn interactions with simulated employees who provide information, approve actions, and revise instructions. Grading combines executable checks of recorded actions and state with model judgments about task requirements, including whether valid alternatives count. Across 1,600 attempts by four models, the authors report cases where correct decisions did not become completed work: agents charged fees twice, split a correct total incorrectly among recipients, or paid while approval was pending. The reported strengths differ by task: Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently.\n\nThe paper’s practical contribution is an evaluation that connects task evidence, agent decisions, and simulated consequences through task-level results and worked examples.","topicIds":["intelligence-and-discovery"],"domain":"science","claimType":"attributed reading","limits":"The evidence is an arXiv abstract; it does not provide the task-level results or worked examples described in the paper. The benchmark uses simulated institutions, so the abstract does not establish how its results correspond to performance in real banking workflows. The authors say they retain the task environments, executable graders, and full trajectories privately to reduce contamination and preserve the benchmark for future evaluations.","speaker":{"name":"Rupawalla, Daniel","roleAtSource":"Article author"},"source":{"title":"Bank-World: A Benchmark for Evaluating Agents on Banking Workflows","publisher":"arXiv cs.AI","format":"Article","url":"https://arxiv.org/abs/2610.39733","publishedAt":"2026-10-29","dateBasis":"Date basis not provided."},"evidence":[{"text":"Rupawalla presents Bank-World as a benchmark of 50 banking tasks across two simulated institutions.","excerpt":"Bank-World is a benchmark of 50 banking tasks across two simulated institutions.","url":"https://arxiv.org/abs/2610.39733","relationship":"Source-stated"},{"text":"The benchmark evaluates workflow steps beyond calculation, including record reconciliation, permission, transactions, and consistent instructions and status reports.","excerpt":"agents must reconcile records, obtain permission, execute transactions, and keep instructions and status reports consistent as circumstances change.","url":"https://arxiv.org/abs/2610.39733","relationship":"Source-stated"},{"text":"Its grading combines executable checks with model judgments, including judgments about valid alternative solutions.","excerpt":"Grading combines executable checks of recorded actions and state with model judgments of task requirements, including whether valid alternative solutions satisfy them.","url":"https://arxiv.org/abs/2610.39733","relationship":"Source-stated"},{"text":"Across 1,600 attempts by four models, the authors report failures in which correct decisions did not become completed work.","excerpt":"Across 1,600 attempts by four models, we find that correct decisions often fail to become completed work.","url":"https://arxiv.org/abs/2610.39733","relationship":"Source-stated"},{"text":"The authors report different strengths across models: Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently.","excerpt":"Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently.","url":"https://arxiv.org/abs/2610.39733","relationship":"Source-stated"},{"text":"The authors say the benchmark makes model differences inspectable through task-level results and worked examples connecting evidence, decisions, and simulated consequences.","excerpt":"task-level results and worked examples connecting source evidence, agent decisions, and simulated consequences.","url":"https://arxiv.org/abs/2610.39733","relationship":"Source-stated"}],"sourceMedia":{"status":"not_found","sourceUrl":"https://arxiv.org/abs/2610.39733","checkedAt":"2026-11-12T05:58:09.118Z","items":[],"note":"No suitable media was found by the supported page extraction."},"assumptions":[],"openQuestion":{"attribution":"Open question","text":"How well would the reported task-level differences predict agents’ performance in real banking workflows, beyond these simulated institutions?"},"whatWouldChangeView":{"attribution":"Change condition not recorded","text":""},"editorialComparisons":[],"live":{"title":"Daniel Rupawalla presents Bank-World, a benchmark for banking workflows","summary":"Daniel Rupawalla presents Bank-World as a benchmark for testing whether agents can complete banking workflows in two simulated institutions. The paper argues that getting a calculation right is not enough: agents must reconcile records, obtain permission, execute transactions, and keep instructions and status reports consistent as circumstances change.\n\nBank-World tests single-turn assignments and multi-turn interactions with simulated employees who provide information, approve actions, and revise instructions. Grading combines executable checks of recorded actions and state with model judgments about task requirements, including whether valid alternatives count. Across 1,600 attempts by four models, the authors report cases where correct decisions did not become completed work: agents charged fees twice, split a correct total incorrectly among recipients, or paid while approval was pending. The reported strengths differ by task: Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently.\n\nThe paper’s practical contribution is an evaluation that connects task evidence, agent decisions, and simulated consequences through task-level results and worked examples.","question":"How well would the reported task-level differences predict agents’ performance in real banking workflows, beyond these simulated institutions?","claims":[{"text":"Rupawalla presents Bank-World as a benchmark of 50 banking tasks across two simulated institutions.","excerpt":"Bank-World is a benchmark of 50 banking tasks across two simulated institutions.","support":"source-stated"},{"text":"The benchmark evaluates workflow steps beyond calculation, including record reconciliation, permission, transactions, and consistent instructions and status reports.","excerpt":"agents must reconcile records, obtain permission, execute transactions, and keep instructions and status reports consistent as circumstances change.","support":"source-stated"},{"text":"Its grading combines executable checks with model judgments, including judgments about valid alternative solutions.","excerpt":"Grading combines executable checks of recorded actions and state with model judgments of task requirements, including whether valid alternative solutions satisfy them.","support":"source-stated"},{"text":"Across 1,600 attempts by four models, the authors report failures in which correct decisions did not become completed work.","excerpt":"Across 1,600 attempts by four models, we find that correct decisions often fail to become completed work.","support":"source-stated"},{"text":"The authors report different strengths across models: Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently.","excerpt":"Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently.","support":"source-stated"},{"text":"The authors say the benchmark makes model differences inspectable through task-level results and worked examples connecting evidence, decisions, and simulated consequences.","excerpt":"task-level results and worked examples connecting source evidence, agent decisions, and simulated consequences.","support":"source-stated"}],"limitations":["The evidence is an arXiv abstract; it does not provide the task-level results or worked examples described in the paper.","The benchmark uses simulated institutions, so the abstract does not establish how its results correspond to performance in real banking workflows.","The authors say they retain the task environments, executable graders, and full trajectories privately to reduce contamination and preserve the benchmark for future evaluations."],"mediaId":"f9665e77a058fd7ace3304eab7951bb8e78feb9dd954757425b07ebf404d35b0","correctionReason":null,"id":"517f025428a8e9a7f1eadab615def84b13829e87b93352695ff671852866d0b2","publicationId":"0a6a8906-7259-48f0-8854-19340372aaf1","version":1,"sourceUrl":"https://arxiv.org/abs/2610.39733","sourceTitle":"Bank-World: A Benchmark for Evaluating Agents on Banking Workflows","publisher":"arXiv cs.AI","publishedAt":null,"originalPublished":{"value":"2026-10-29","precision":"day","basis":"publisher_citation_date"},"firstObservedAt":"2026-10-30T06:43:03.996Z","createdAt":"2026-11-11T12:54:59.606Z","historical":true,"entityIds":["arxiv"],"topicIds":["intelligence-and-discovery"],"media":[{"id":"f9665e77a058fd7ace3304eab7951bb8e78feb9dd954757425b07ebf404d35b0","kind":"article","url":"https://arxiv.org/abs/2610.39733","sourceUrl":"https://arxiv.org/abs/2610.39733","label":"Read original","provenance":"source_link","verification":{"status":"verified","checkedAt":"2026-10-31T06:31:17.473Z","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/2610.39733","checkedAt":"2026-11-12T05:58:09.118Z","items":[],"note":"No suitable media was found by the supported page extraction."},"editorialDecision":{"outcome":"accept","reasonCodes":["material_development"],"rubricVersion":"stream-admission-v5","mediaId":"f9665e77a058fd7ace3304eab7951bb8e78feb9dd954757425b07ebf404d35b0","confidence":0.8200000000000001,"provider":"typesafe","model":"jev-1.13.0","inputHash":"0799b50c56de77767ad0967ffdf3e862341474b54a1e2309f1c022d5dc8a6d50","decidedAt":"2026-10-31T06:31:19.143Z"},"provenance":{"textHash":"f0983f6d8b89353e05493386c541f148b0ff3e0d9c8352771c0276afe3404d5f","observationId":"ecd7ba3eaf27ca01a13acaed4d384fe57d8f666716a17fda63b19eb47c43f339","retrievedAt":"2026-10-31T06:31:17.187Z","kind":"publisher-page","preparer":{"model":"gpt-6-luna","runId":"d4a3eaa8-c59b-4ba4-8392-9b42a53f3cd3"},"reviewer":{"model":"gpt-6-luna","runId":"1802dfcd-b0ee-43e9-8e5a-183d40b446fe"}},"audit":{"status":"uncertain","reviewedAt":"2026-11-11T12:54:59.606Z","model":"anthropic/claude-opus-5.5"},"sourceAttribution":{"authors":[{"name":"Rupawalla, Daniel","url":null,"kind":"unknown"}],"authorRole":"article-author","hosts":[],"status":"stated","authorRoster":{"truncated":false,"omitted":0,"assertionGroupsOmitted":0},"participation":[{"actor":{"name":"Rupawalla, Daniel","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Rupawalla, Daniel","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2610.39733","locator":"head/meta[name=author|citation_author]"},"assertionId":"32b91507f283d8f91003ed28d244190ce663c583f67e9d2b4244f1b3036af45c:participation:0","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-12T05:58:09.118Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"32b91507f283d8f91003ed28d244190ce663c583f67e9d2b4244f1b3036af45c","sourceUrl":"https://arxiv.org/abs/2610.39733","contentSha256":"c9ca6cfa663025ea62aadd1ec891b1a88869d409284a87ad63c850459082896e","textHash":"f0983f6d8b89353e05493386c541f148b0ff3e0d9c8352771c0276afe3404d5f","observedAt":"2026-11-12T05:58:09.118Z"}}],"participationCoverage":{"total":1,"returned":1,"complete":true,"fullAssertions":"source-metadata-endpoint"},"distribution":null,"publisher":null,"sourceUrl":"https://arxiv.org/abs/2610.39733","snapshotId":"32b91507f283d8f91003ed28d244190ce663c583f67e9d2b4244f1b3036af45c","contentSha256":"c9ca6cfa663025ea62aadd1ec891b1a88869d409284a87ad63c850459082896e","textHash":"f0983f6d8b89353e05493386c541f148b0ff3e0d9c8352771c0276afe3404d5f","observedAt":"2026-11-12T05:58:09.118Z","basis":"publisher-page-metadata","sourceLinks":43,"linksTruncated":false,"metadataUrl":"/api/pipeline/stream/517f025428a8e9a7f1eadab615def84b13829e87b93352695ff671852866d0b2/source"}}}],"audits":[{"publicationId":"0a6a8906-7259-48f0-8854-19340372aaf1","verdict":"uncertain","findings":[{"dimension":"attribution","status":"pass","explanation":"The benchmark and findings are correctly attributed to the paper by Daniel Rupawalla, the sole listed author. The draft's plural 'the authors' mirrors the abstract's 'we' and does not misattribute the claims. Findings stay framed as reported results.","excerpt":"Authors:Daniel Rupawalla"},{"dimension":"summary","status":"uncertain","explanation":"Central terms go unexplained for a general reader. These include 'agents' (AI systems taking actions), 'benchmark', 'single-turn' versus 'multi-turn', and 'contamination' in the limitations. Sol, Opus and Grok are named but never identified as AI models, so readers lack context. The summary also says 'cases where' correct decisions did not become completed work, which drops the abstract's 'often'. Smallest repairs: add brief plain-language definitions or tooltips for these terms, and restore 'often'.","excerpt":"we find that correct decisions often fail to become completed work"},{"dimension":"date","status":"pass","explanation":"originalPublished 2026-10-29 matches the arXiv v1 submission date. It is not the later feed date.","excerpt":"[Submitted on 29 Oct 2026]"},{"dimension":"support","status":"pass","explanation":"Each claim matches the abstract's wording: the 50 tasks, the workflow requirements, the grading approach, 1,600 attempts, the failure examples, model strengths and private retention. The question appropriately raises unproven real-world transfer without asserting it. The limitations accurately note the abstract-only evidence and the simulated setting.","excerpt":"Agents charge fees twice, distribute the correct total in incorrect amounts among the recipients, and execute payments while approval is pending."},{"dimension":"media","status":"pass","explanation":"The selected media is the verified direct arXiv abstract page for this paper. It is the most direct access to the source.","excerpt":null}],"createdAt":"2026-11-11T12:54:59.606Z","model":"anthropic/claude-opus-5.5"}],"correctionUrl":"https://escapemeridian.com/corrections/"}