[Submitted on 5 May 2026]
Title:Controllable Narrative Rendering for Enhanced Assisted Writing
View a PDF of the paper titled Controllable Narrative Rendering for Enhanced Assisted Writing, by Mingzhe Lu and 7 other authors
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Abstract:Despite the remarkable proficiency of large language models (LLMs) in basic writing assistance, their utility in creative writing is fundamentally hindered by a persistent binary failure. This issue manifests as an oscillation between safe, surface-level editing, referred to as remedial polishing, and destructive, uncontrolled plot expansion. This dilemma defines a critical trade-off between narrative fidelity and descriptive intensity. We propose Loom, an assisted writing framework grounded in the narratological distinction between story and discourse. Loom employs a three-layer pipeline that operationalizes an intent-centered semiotic chain-of-thought to enforce precise control over narrative intent and rendering density. This architecture separates the generation of perceptual material from syntactic insertion, ensuring that enhancement occurs without violating the original event structure. Our comprehensive evaluation, which includes LLM-based metrics and human assessment, demonstrates that Loom successfully resolves this fundamental tension. Loom achieves the highest overall quality score, yielding substantial gains in factual integrity and descriptive intensity compared to state-of-the-art baselines.
Subjects:
Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2607.00009 [cs.CL]
(or arXiv:2607.00009v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2607.00009
arXiv-issued DOI via DataCite
Submission history
From: Mingzhe Lu [view email] [v1] Tue, 5 May 2026 00:35:45 UTC (4,631 KB)
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