Silent Misalignment in Multimodal Generative System: A Trace-Based Analysis of Cross-Turn State Drift in Text–Image Workflows

Fuente: Zenodo
Enregistré dans:
Détails bibliographiques
Auteur principal: Ma, Sincere Ann
Format: Recurso digital
Langue:anglais
Publié: Zenodo 2026
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866901173482553344
author Ma, Sincere Ann
author_facet Ma, Sincere Ann
contents <p><span>This working paper reports a trace-based field analysis of a multimodal generative workflow in which textual coherence and visual artefact integrity diverged across turns. In a long-horizon design scenario (text–image co-generation for a future-city concept), the language layer maintained high semantic continuity and repeatedly confirmed constraints, while the image outputs drifted across iterations—exhibiting palette dominance, region-programme misalignment, and label-only “corrections” without underlying structural compliance.</span></p> <p> </p> <p><span>The paper argues that the core issue is not best framed as model “accuracy” or single-turn prompt sensitivity. Instead, it is a governance failure of cross-modal state control: the interaction lacks non-bypassable mechanisms for state-locking, cross-modal verification, and mismatch visibility. The analysis is intentionally vendor- and model-agnostic, treating the observed pattern as a structural risk that can plausibly recur across systems with different epistemic positioning, consistent with parallel false-completion and artefact-mismatch incidents in AI-mediated document workflows.</span></p> <p> </p> <p><span>Supporting evidence (full trace logs, screenshots, and time-ordered notes) is preserved. This working paper does not include raw materials; a later revision will include an anonymised trace index and selected excerpts under appropriate disclosure constraints.</span></p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18221463
institution Zenodo
language eng
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Silent Misalignment in Multimodal Generative System: A Trace-Based Analysis of Cross-Turn State Drift in Text–Image Workflows
Ma, Sincere Ann
multimodal generative AI; human–AI interaction; cross-turn drift; state governance; artefact integrity; cross-modal verification; silent misalignment; palette dominance; process-trace analysis; workflow reliability; interaction-level control
<p><span>This working paper reports a trace-based field analysis of a multimodal generative workflow in which textual coherence and visual artefact integrity diverged across turns. In a long-horizon design scenario (text–image co-generation for a future-city concept), the language layer maintained high semantic continuity and repeatedly confirmed constraints, while the image outputs drifted across iterations—exhibiting palette dominance, region-programme misalignment, and label-only “corrections” without underlying structural compliance.</span></p> <p> </p> <p><span>The paper argues that the core issue is not best framed as model “accuracy” or single-turn prompt sensitivity. Instead, it is a governance failure of cross-modal state control: the interaction lacks non-bypassable mechanisms for state-locking, cross-modal verification, and mismatch visibility. The analysis is intentionally vendor- and model-agnostic, treating the observed pattern as a structural risk that can plausibly recur across systems with different epistemic positioning, consistent with parallel false-completion and artefact-mismatch incidents in AI-mediated document workflows.</span></p> <p> </p> <p><span>Supporting evidence (full trace logs, screenshots, and time-ordered notes) is preserved. This working paper does not include raw materials; a later revision will include an anonymised trace index and selected excerpts under appropriate disclosure constraints.</span></p>
title Silent Misalignment in Multimodal Generative System: A Trace-Based Analysis of Cross-Turn State Drift in Text–Image Workflows
topic multimodal generative AI; human–AI interaction; cross-turn drift; state governance; artefact integrity; cross-modal verification; silent misalignment; palette dominance; process-trace analysis; workflow reliability; interaction-level control
url https://doi.org/10.5281/zenodo.18221463