Data-Driven Persona-Conditioned Agents for A/B Test Simulation

arXiv:2609.01038 · cs.AI · Submitted 2026-09-01 · Read on arXiv

cs.AI

Submitted: 2026-09-01

Updated: 2026-09-01

Comments: Work accepted at EMNLP 2026 Industry Track

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

Terminology

• Accuracy — 42× in this paper · explained in 1 episode
• Alignment — 22× in this paper · explained in 1 episode
• Benchmark — 20× in this paper · explained in 2 episodes
• Grounding — 5× in this paper · explained in 3 episodes
• Personalization — 4× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Trace — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Aggregation — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Core — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Pairwise Comparisons — 2× in this paper · explained in 2 episodes
• Positional Bias — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• Wasserstein Distance — 2× in this paper · explained in 4 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Sycophancy — 1× in this paper · explained in 4 episodes
• Vector Representations — 1× in this paper · explained in 2 episodes

Sources

• SimGym: Traffic-Grounded Browser Agents for Offline A/B Testing in E-Commerce
• From Persona to Personalization: A Survey on Role-Playing Language Agents
• Super-Samples from Kernel Herding
• Scaling Synthetic Data Creation with 1,000,000,000 Personas
• Personalization Increases Affective Alignment but Has Role-Dependent Effects on Epistemic Independence in LLMs
• LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals
• SimAB: Simulating A/B Tests with Persona-Conditioned AI Agents for Rapid Design Evaluation
• Different Demographic Cues Yield Inconsistent Conclusions About LLM Personalization and Bias

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