{"ID":2837567,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.19123","arxiv_id":"2511.19123","title":"Facilitating the Integration of LLMs Into Online Experiments With Simple Chat","abstract":"As large language models (LLMs) become increasingly prevalent, understanding human-LLM interactions is emerging as a central priority in psychological research. Online experiments offer an efficient means to study human-LLM interactions, yet integrating LLMs into established survey platforms remains technically demanding, particularly when aiming for ecologically valid, real-time conversational experiences with strong experimental control. We introduce Simple Chat, an open-source, research-focused chat interface that streamlines LLM integration for platforms such as Qualtrics, oTree, and LimeSurvey, while presenting a unified participant experience across conditions. Simple Chat connects to both commercial providers and open-weights models, supports streaming responses to preserve conversational flow, and offers an administrative interface for fine-grained control of prompts and interface features. By reducing technical barriers, standardizing interfaces, and improving participant experience, Simple Chat helps advance the study of human-LLM interaction. In this article, we outline Simple Chat's key features, provide a step-by-step tutorial, and demonstrate its utility through two illustrative case studies.","short_abstract":"As large language models (LLMs) become increasingly prevalent, understanding human-LLM interactions is emerging as a central priority in psychological research. Online experiments offer an efficient means to study human-LLM interactions, yet integrating LLMs into established survey platforms remains technically demandi...","url_abs":"https://arxiv.org/abs/2511.19123","url_pdf":"https://arxiv.org/pdf/2511.19123v2","authors":"[\"R. Bermudez Schettino\",\"A. Dasmeh\",\"L. Brinkmann\"]","published":"2025-11-24T13:52:42Z","proceeding":"cs.HC","tasks":"[\"cs.HC\",\"cs.CY\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}