MemSlides: A Hierarchical Memory Driven Agent Framework for Personalized Slide Generation with Multi-turn Local Revision
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Computer Science > Computation and Language
arXiv:2606.17162 (cs)
[Submitted on 15 Jun 2026]
Title:MemSlides: A Hierarchical Memory Driven Agent Framework for Personalized Slide Generation with Multi-turn Local Revision
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Abstract:Personalized presentation generation requires more than conditioning on a current prompt or template: agents must preserve stable user preferences across tasks, retain newly introduced preferences and constraints during multi-turn revision, and carry out local edits reliably. We propose MemSlides, a hierarchical memory framework for personalized presentation agents that separates long-term memory from working memory and further divides long-term memory into user profile memory and tool memory. User profile memory stores intent-conditioned profiles for round-0 personalization, working memory carries active preferences and session constraints across revision rounds, and tool memory stores reusable execution experience for reliable localized editing. MemSlides pairs this memory design with scoped slide-local revision, so targeted updates act on the smallest affected region instead of repeatedly regenerating the full deck. In controlled experiments, user profile memory improves persona-alignment judgments on a multi-persona, multi-intent profile bank, tool-memory injection improves closed-loop modify behavior in diagnostic matched-pair settings, and qualitative cases illustrate working memory's ability to carryover preferences. Taken together, these results suggest that effective personalization in presentation authoring depends on separating persistent user profiles, session-level working memory, and reusable execution experience across generation and localized revision.
| Comments: | Code, website, project page, and video are linked in the paper |
| Subjects: | Computation and Language (cs.CL); Human-Computer Interaction (cs.HC); Multiagent Systems (cs.MA) |
| Cite as: | arXiv:2606.17162 [cs.CL] |
| (or arXiv:2606.17162v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2606.17162
arXiv-issued DOI via DataCite (pending registration)
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View a PDF of the paper titled MemSlides: A Hierarchical Memory Driven Agent Framework for Personalized Slide Generation with Multi-turn Local Revision, by Ye Jin and 3 other authors
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