A Universal Cliff and a Design Fingerprint: Cross-Section Defect Detection Under LLM Orchestration
The paper discusses the challenges of detecting cross-section defects in documents processed by language model systems. It identifies a significant drop in detection capability when models operate under orchestration compared to single-agent scenarios. The findings reveal that the most aligned systems may not be the safest, highlighting structural issues in defect detection.
- ▪A universal detection cliff is observed, where models lose the ability to find cross-section defects under orchestration.
- ▪Detection capability falls by two-thirds or more across various tested paradigms.
- ▪Only one developer's model shows improvement in defect detection as alignment strengthens, but it also raises false alarms.
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Record
| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.26174 |
| Publication time | Wed, 27 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-27T04:07:56.398Z |
| Last seen | 2026-05-27T04:07:56.398Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | REfQ6qh3Fgsk |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Software Engineering arXiv:2605.26174 (cs) [Submitted on 25 May 2026] Title:A Universal Cliff and a Design Fingerprint: Cross-Section Defect Detection Under LLM Orchestration Authors:Hiroki Fukui View a PDF of the paper titled A Universal Cliff and a Design Fingerprint: Cross-Section Defect Detection Under LLM Orchestration, by Hiroki Fukui View PDF HTML (experimental) Abstract:Production language-model systems answer a request by partitioning it across an invisible orchestration of worker agents that recompose one integrated report. We ask what this does to a class of defect no single worker can see: a contradiction in the relation between two distant sections of a document.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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