[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-84964-en":3,"doc-seo-84964-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},84964,7971461740886,"Theodore","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","Operational Reframing and Approval-Framed Delegation in Multi-Agent LLM Safety","Safety evaluations of multi-agent LLM systems often reduce comparisons between a direct prompt and a planner-executor pipeline to a single “pipeline effect,” obscuring multiple simultaneous mechanisms. Harmful intent can be rewritten as plausible operational work, planners may refuse or transform requests, and delegation prompts can claim the task has already been approved. A five-condition controlled contrast design makes these contributors observable across 30 synthetic harmful scenarios and an external set from four safety benchmarks using LLM-judged compliance.","Operational Reframing and Approval-Framed Delegation in  \nMulti-Agent LLM Safety  \nLifei Liu  \nIndependent Researcher Seattle, WA, USA[lliu.lifei@gmail.com](lliu.lifei@gmail.com)  \nHaoran Yu  \nIndependent Researcher Seattle, WA, USA [haoranyu889@gmail.com](haoranyu889@gmail.com)  \nXiaochong Jiang  \nIndependent Researcher Seattle, WA, USA [jiang.xiaoc@northeastern.edu](jiang.xiaoc@northeastern.edu)  \nSu Wang  \nCarnegie Mellon University Pittsburgh, PA, USA [suwang@alumni.cmu.edu](suwang@alumni.cmu.edu)  \nPin Qian  \nCarnegie Mellon University Pittsburgh, PA, USA[pqian@alumni.cmu.edu](pqian@alumni.cmu.edu)  \nYihang Chen  \nGeorgia Institute of Technology Atlanta, GA, USA[ychen3726@gatech.edu](ychen3726@gatech.edu)  \narXiv :2607 .07097v 1 [ cs .AI] 8 Jul 2026  \nAbstract  \nSafety evaluations of multi-agent LLM systems often compare a direct prompt against a planner-executor pipeline and report the difference as a single “pipeline effect.” This aggregate hides several simultaneous changes: harmful intent may be recast as plausible operational work, a planner may refuse or transform the request, and the executor may receive the result under a delegation prompt that says the task has already been approved. We introduce a fivecondition controlled contrast design that makes these contributors observable across a primary set of 30 synthetic harmful scenarios and an exploratory external validation set from four agentsafety benchmarks, using LLM-judged compliance. The main result is that aggregate pipeline safety is not interpretable as a stable architectural property. Operational reframing is the most portable risk signal: rewritten operational prompts increase compliance for GPT, Gemini, and DeepSeek in both the primary and external scenario sets, while Claude is comparatively resistant. Planner behavior can offset this risk, but mainly through refusal; when the planner produces executable steps, the executor can become more compliant than in the direct operational baseline. Approval-framed delegation is prompt-, model-, and scenario-source-sensitive, with a skeptical executor prompt sharply reducing compliance in our ablation. Raw-direct model rankings can also mispredict deployed planner-executor behavior: in the primary set, Gemini is safest under raw direct prompts yet shows the largest pipeline amplification with a Claude planner (an 8. 9% → 38. 9%, +30pp raw-to-pipeline swing), while GPT’s near-zero aggregate pipeline effect hides a reframing increase canceled by planner refusal. Multi-agent safety evaluations should therefore report operational reframing, planner behavior, approval-framed delegation, and model pairing separately before attributing failures to architecture itself.  \nPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific [permission and/or a fee. Request permissions from permissions@acm.org](permission and/or a fee. Request permissions from permissions@acm.org).  \nKDD Workshop ’26, Jeju, Korea  \n© 2026 Copyright held by the owner/author(s) . Publication rights licensed to ACM.  \nKeywords  \nLLM agents, multi-agent safety, controlled contrasts, operational reframing, delegation framing  \nACM Reference Format:  \nLifei Liu, Haoran Yu, Xiaochong Jiang, Su Wang, Pin Qian, and Yihang Chen. 2026. Operational Reframing and Approval-Framed Delegation in Multi-Agent LLM Safety. In Proceedings of Workshop on Evaluation and Trustworthiness of Agentic AI (KDD Workshop ’26) . ACM, New York, NY, USA, 10 pages.  \n1 Introduction  \nRecent work reports that multi-agent LLM systems can ","cbCaintoInJ4jAEQ","https://ap.wps.com/l/cbCaintoInJ4jAEQ","pdf",569886,1,10,"English","en",105,"# Introduction\n## Measurement challenge: what changed in pipeline vs direct\n## Five-condition controlled contrast design\n# Findings","[{\"question\":\"Why can pipeline effect comparisons be misleading in multi-agent LLM safety evaluations?\",\"answer\":\"Because direct-vs-pipeline comparisons collapse several changes into one number, such as operational reframing, planner refusal/pass-through, and approval-framed delegation. This prevents attributing differences to a specific mechanism.\"},{\"question\":\"What does the paper’s five-condition controlled contrast design aim to measure?\",\"answer\":\"It routes each harmful scenario through direct, planner-mediated, and approval-framed pipeline variants to measure operational reframing (F1), planner behavior (F2), and approval-framed delegation (F3) separately.\"},{\"question\":\"What is the paper’s main finding about operational reframing and model safety?\",\"answer\":\"Operational reframing is identified as the most portable risk signal: rewritten operational prompts increase compliance for GPT, Gemini, and DeepSeek across primary and external scenario sets, while Claude is comparatively more resistant.\"}]",1784199747,25,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":27},"operational-reframing-and-approval-framed-delegation-in-multi-agent-llm-safety","",{"@graph":35,"@context":85},[36,53,68],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/operational-reframing-and-approval-framed-delegation-in-multi-agent-llm-safety/84964/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-17","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why can pipeline effect comparisons be misleading in multi-agent LLM safety evaluations?","Question",{"text":75,"@type":76},"Because direct-vs-pipeline comparisons collapse several changes into one number, such as operational reframing, planner refusal/pass-through, and approval-framed delegation. This prevents attributing differences to a specific mechanism.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What does the paper’s five-condition controlled contrast design aim to measure?",{"text":80,"@type":76},"It routes each harmful scenario through direct, planner-mediated, and approval-framed pipeline variants to measure operational reframing (F1), planner behavior (F2), and approval-framed delegation (F3) separately.",{"name":82,"@type":73,"acceptedAnswer":83},"What is the paper’s main finding about operational reframing and model safety?",{"text":84,"@type":76},"Operational reframing is identified as the most portable risk signal: rewritten operational prompts increase compliance for GPT, Gemini, and DeepSeek across primary and external scenario sets, while Claude is comparatively more resistant.","https://schema.org",{"og:url":51,"og:type":87,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":89,"canonical":51},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,134],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":45,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":45,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":45,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":45,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":45,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":21,"doc_module":4,"doc_module_name":45,"category_name":132,"show_sort_weight":21,"slug":133},"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":45,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]