arXiv AI
Integrating Large Language Models with Human Data to Design Personalized Decoy Nudges
Read the original on arXiv AI →The Flow has not summarised this story yet — read it at arXiv AI.
Related stories
arXiv AI
1d ago
Decision Models as Scalable Economic Surrogates that Capture Human Variation
Decision Models (DMs) are a new class of AI models that provide fast responses and output a probability distribution over a fixed set of options. In a first evaluation, 10 DMs were compared with 8 Large Language Models (LLMs) across three economic settings—a household spending survey, classic economic games, and a labour‑market field experiment. Frontier DMs, those scoring highest on general decision‑making benchmarks, reproduced human response variation more closely than LLMs in all settings, matched LLMs on modal responses in the spending survey, and were roughly ten times faster and over a hundred times cheaper than the fastest LLM.
arXiv AI
Jun 17
Statistical Foundations of LLM-based A/B Testing: A Surrogacy Framework for Human Causal Inference
arXiv:2606. 17165v1 Announce Type: cross Abstract: Organizations and researchers show increasing interest in using large language models (LLMs) in place of human participants in A/B tests, in the hope of experimenting faster and at lower cost.
arXiv AI
Jul 31
When Synthetic Users Fail: A Cross-Domain Benchmark of LLM-Simulated Human Survey Responses
arXiv:2607. 26348v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as synthetic users, stand-ins for human respondents whose simulated answers feed product, policy, and market decisions.
arXiv AI
Jun 17
Would a Large Language Model Pay Extra for a View? Inferring Willingness to Pay from Subjective Choices
arXiv:2602. 09802v2 Announce Type: replace Abstract: As Large Language Models (LLMs) are increasingly deployed in applications such as travel assistance and purchasing support, they are often required to make subjective choices on behalf of users in settings where no objectively correct answer exists.
arXiv AI
Jul 7
Mecha-nudges for Machines
arXiv:2603. 23433v3 Announce Type: replace Abstract: AI agents are becoming active decision-makers on the Internet.
Hugging Face Trending Papers
Jul 13
Reproducing human biases in route choice using large language models: Toward scalable behavioral modeling
Human choice behavior, including route choice, exhibits systematic behavioral biases that deviate from the assumptions of full rationality. Cumulative prospect theory (CPT) has been widely recognized as an effective framework for characterizing such behavioral patterns.