LLMs Corrupt Your Documents When You Delegate

Computer Science > Computation and Language arXiv:2604.15597 (cs) [Submitted on 17 Apr 2026] Title:LLMs Corrupt Your Documents When You Delegate Authors:Philippe Laban, Tobias Schnabel, Jennifer Neville View a PDF of the paper titled LLMs Corrupt Your Documents When You Delegate, by Philippe Laban and Tobias Schnabel and Jennifer Neville View PDF HTML (experimental) Abstract:Large Language Models (LLMs) are poised to disrupt knowledge work, with the emergence of delegated work as a new interaction paradigm (e.g., vibe coding). Delegation requires trust - the expectation that the LLM will faithfully execute the task without introducing errors into documents. We introduce DELEGATE-52 to study the readiness of AI systems in delegated workflows. DELEGATE-52 simulates long delegated workflows that require in-depth document editing across 52 professional domains, such as coding, crystallography, and music notation. Our large-scale experiment with 19 LLMs reveals that current models degrade documents during delegation: even frontier models (Gemini 3.1 Pro, Claude 4.6 Opus, GPT 5.4) corrupt an average of 25% of document content by the end of long workflows, with other models failing more severely. Additional experiments reveal that agentic tool use does not improve performance on DELEGATE-52, and that degradation severity is exacerbated by document size, length of interaction, or presence of distractor files. Our analysis shows that current LLMs are unreliable delegates: they introduce sparse but severe errors that silently corrupt documents, compounding over long interaction. Subjects: Computation and Language (cs.CL); Human-Computer Interaction (cs.HC) Cite as: arXiv:2604.15597 [cs.CL] (or arXiv:2604.15597v1 [cs.CL] for this version) https://doi.org/10.48550/arXiv.2604.15597 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Philippe Laban [view email] [v1] Fri, 17 Apr 2026 00:33:32 UTC (9,982 KB) Full-text links: Access Paper: View a PDF of the paper titled LLMs Corrupt Your Documents When You Delegate, by Philippe Laban and Tobias Schnabel and Jennifer NevilleView PDFHTML (experimental)TeX Source view license Current browse context: cs.CL < prev | next > new | recent | 2026-04 Change to browse by: cs cs.HC References & Citations NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs…

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