Seeing Is Not Perceiving: When Synthetic Consumers Can and Cannot Pretest Visual Marketing

arXiv:2609.25677 · cs.AI, cs.CY, econ.GN, q-fin.EC · Submitted 2026-09-22 · Read on arXiv

cs.AI, cs.CY, econ.GN, q-fin.EC

Submitted: 2026-09-22

Updated: 2026-09-22

Comments: 58 pages (30 pages of main text, 23 pages of appendix), 18 figures, 25 tables. All six studies were preregistered on AsPredicted

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 64× in this paper · explained in 2 episodes
• Alignment — 15× in this paper · explained in 1 episode
• Steering — 15× in this paper · explained in 2 episodes
• Generative AI — 11× in this paper · explained in 2 episodes
• Calibration — 10× in this paper · explained in 7 episodes
• In-Context Learning — 9× in this paper · explained in 4 episodes
• Clustering — 8× in this paper · explained in 2 episodes
• Robustness — 7× in this paper · explained in 5 episodes
• AI Agents — 4× in this paper · explained in 2 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Bayesian Inference — 3× in this paper · explained in 5 episodes
• Digital Twin — 3× in this paper · explained in 5 episodes
• In-Context Learning (ICL) — 3× in this paper · explained in 5 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Perceptual Alignment — 2× in this paper · explained in 2 episodes
• RAG — 2× in this paper · explained in 3 episodes
• Chain-of-Thought (CoT) — 1× in this paper · explained in 4 episodes
• Chain-of-Thought (CoT) Prompting — 1× in this paper · explained in 3 episodes
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Class-based Term Frequency-Inverse Document Frequency — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Parsimony — 1× in this paper · explained in 2 episodes
• Retrieval-Augmented Generation — 1× in this paper
• Retrieval-Augmented Generation (RAG) — 1× in this paper · explained in 16 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• BERTopic: Neural topic modeling with a class-based TF-IDF procedure
• Digital Twins as Funhouse Mirrors: Five Key Distortions

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