迈向缓解虚构共识：多智能体辩论综合的主动溯源门控

Computer Science > Multiagent Systems arXiv:2609.31422 (cs) [Submitted on 25 Sep 2026] Title:Towards Mitigating Fabricated Consensus: The Active Provenance Gate for Multi-Agent Debate Synthesis Authors:Jakub Masłowski, Jarosław A. Chudziak View a PDF of the paper titled Towards Mitigating Fabricated Consensus: The Active Provenance Gate for Multi-Agent Debate Synthesis, by Jakub Mas{\l}owski and 1 other authors View PDF HTML (experimental) Abstract:Large language model-based multi-agent debate (MAD) systems are being increasingly used as complex decision pipelines in distributed processes. However, their final synthesis phase still remains inadequately controlled. Even with detailed debate logs, summarizing models are prone to fabricating smoothly written debate consensus that is not grounded in the debate's history. To address this safety gap, this paper presents empirical research and studies if the introduction of active post-debate verification can mitigate the production of such factually unsupported summaries, while still providing valuable information. Furthermore, it is examined whether explicitly signalling divergence is preferable in the absence of a reliable compromise. The Active Provenance Gate (APG) is introduced as a post-debate verification layer that treats the source as a hard constraint, analysing the debate logs, auditing each claim, and applying self-correction. In crisis simulations, the self-healing mechanism more than doubles the average data Provenance Fidelity in difficult condition scenarios, before the strict gate blocks unsupported claims and generates divergence reports. In the human study, a vast majority of the users (over 75%) preferred a report explicitly stating failure in critical scenarios, despite most of them perceiving fabricated consensus from the baseline system as more fluent. Our main contribution is the transition of data origin tracing from passive logging to active conditional blocking before publication. Comments: Subjects: Multiagent Systems (cs.MA); Artificial Intelligence (cs.AI); Computation and Language (cs.CL) ACM classes: I.2.11; I.2.7 Cite as: arXiv:2609.31422 [cs.MA] (or arXiv:2609.31422v1 [cs.MA] for this version) https://doi.org/10.48550/arXiv.2609.31422 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Jakub Masłowski [view email] [v1] Fri, 25 Sep 2026 15:44:18 UTC (638 KB) Full-text links: Access Paper: View a PDF of the paper titled Towards Mitigating Fabricated Consensus: The Active Provenance Gate for Multi-Agent Debate Synthesis, by Jakub Mas{\l}owski and 1 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.MA new | recent | 2026-09 Change to browse by: cs cs.AI cs.CL References & Citations NASA ADS Google 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 arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)