AI RESEARCH
Can large language models assist choice modelling? Insights into prompting strategies and current models capabilities
arXiv CS.AI
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ArXi:2507.21790v2 Announce Type: replace-cross Large Language Models (LLMs) are becoming widely used to various workflows across different disciplines, yet their potential in discrete choice modelling remains relatively unexplored. This work examines the potential of LLMs as assistive agents in the specification and, where technically feasible, estimation of Multinomial Logit models. We implement a systematic experimental framework involving twelve versions of seven leading LLMs (ChatGPT, Claude, DeepSeek, Gemini, Gemma, Llama, and Mistral) evaluated under five experimental configurations.