# MindFuse: Towards GenAI Explainability in Marketing Strategy Co-Creation

arXiv: https://arxiv.org/abs/2512.04112 · HTML: https://mlsanity.com/paper/2512.04112/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 71 references that are in the map.
- First posted on arXiv 1 Dec 2025.

## Builds on (most cited first, 15 of 15)

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- [Linformer: Self-Attention with Linear Complexity](https://mlsanity.com/paper/2006.04768/) (2020)
- [Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models](https://mlsanity.com/paper/2402.17177/) (2024)
- [Text and Code Embeddings by Contrastive Pre-Training](https://mlsanity.com/paper/2201.10005/) (2022)
- [Mega: Moving Average Equipped Gated Attention](https://mlsanity.com/paper/2209.10655/) (2022)
- [Hallucination Detection: Robustly Discerning Reliable Answers in Large Language Models](https://mlsanity.com/paper/2407.04121/) (2024)
- [Representation Learning-Assisted Click-Through Rate Prediction](https://mlsanity.com/paper/1906.04365/) (2019)
- [Personality-Driven Social Multimedia Content Recommendation](https://mlsanity.com/paper/2207.12236/) (2022)
- [SoMin.ai: Personality-Driven Content Generation Platform](https://mlsanity.com/paper/2011.14615/) (2020)
- [I Know Where You Are Coming From: On the Impact of Social Media Sources on AI Model Performance](https://mlsanity.com/paper/2002.01726/) (2020)
- [Against Opacity: Explainable AI and Large Language Models for Effective Digital Advertising](https://mlsanity.com/paper/2504.20064/) (2025)
- [Two-Faced Humans on Twitter and Facebook: Harvesting Social Multimedia for Human Personality Profiling](https://mlsanity.com/paper/2106.10673/) (2021)

## Abstract (arXiv)

The future of digital marketing lies in the convergence of human creativity and generative AI, where insight, strategy, and storytelling are co-authored by intelligent systems. We present MindFuse, a brave new explainable generative AI framework designed to act as a strategic partner in the marketing process. Unlike conventional LLM applications that stop at content generation, MindFuse fuses CTR-based content AI-guided co-creation with large language models to extract, interpret, and iterate on communication narratives grounded in real advertising data. MindFuse operates across the full marketing lifecycle: from distilling content pillars and customer personas from competitor campaigns to recommending in-flight optimizations based on live performance telemetry. It uses attention-based explainability to diagnose ad effectiveness and guide content iteration, while aligning messaging with strategic goals through dynamic narrative construction and storytelling. We introduce a new paradigm in GenAI for marketing, where LLMs not only generate content but reason through it, adapt campaigns in real time, and learn from audience engagement patterns. Our results, validated in agency deployments, demonstrate up to 12 times efficiency gains, setting the stage for future integration with empirical audience data (e.g., GWI, Nielsen) and full-funnel attribution modeling. MindFuse redefines AI not just as a tool, but as a collaborative agent in the creative and strategic fabric of modern marketing.