title: "I Want It That Way": Enabling Interactive Decision Support Using Large
    Language Models and Constraint Programming
summary: A critical factor in the success of decision support systems is the accurate
  modeling of user preferences. Psychology research has demonstrated that users
  often develop their preferences during the elicitation process, highlighting
  the pivotal role of system-user interaction in developing personalized systems.
  This paper introduces a novel approach, combining Large Language Models (LLMs)
  with Constraint Programming to facilitate interactive decision support. We
  study this hybrid framework through the lens of meeting scheduling, a
  time-consuming daily activity faced by a multitude of information workers. We
  conduct three studies to evaluate the novel framework, including a diary study
  (n=64) to characterize contextual scheduling preferences, a quantitative
  evaluation of the system's performance, and a user study (n=10) with a
  prototype system. Our work highlights the potential for a hybrid LLM and
  optimization approach for iterative preference elicitation and design
  considerations for building systems that support human-system collaborative
  decision-making processes.
paper_authors._id: 65791c3f1bf8e371c4fde7df
paper_authors.name: Connor Lawless
paper_authors._id: 65791c3f1bf8e371c4fde7e0
paper_authors.name: Jakob Schoeffer
paper_authors._id: 65791c3f1bf8e371c4fde7e1
paper_authors.name: Lindy Le
paper_authors._id: 65791c3f1bf8e371c4fde7e2
paper_authors.name: Kael Rowan
paper_authors._id: 65791c3f1bf8e371c4fde7e3
paper_authors.name: Shilad Sen
paper_authors._id: 65791c3f1bf8e371c4fde7e4
paper_authors.name: Cristina St. Hill
paper_authors._id: 65791c3f1bf8e371c4fde7e5
paper_authors.name: Jina Suh
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-12-13T11:00:15.150Z
paper_authors._id: 645481fbcd09ceba0e16dd12
paper_authors.avatarUrl: /avatars/b2b8a92d5877a0c60e890f714f6d955a.svg
paper_authors.fullname: Jina Suh
paper_authors.type: user
paper_authors.user: jinasuh
paper_authors._id: 65791c3f1bf8e371c4fde7e6
paper_authors.name: Bahar Sarrafzadeh
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-12-14T10:34:57.023Z
paper_authors._id: 657a5ccef7d26c50c40ccf23
paper_authors.avatarUrl: /avatars/d57162831554f95d55bae85689ad7a29.svg
paper_authors.fullname: Bahareh Sarrafzadeh
paper_authors.type: user
paper_authors.user: Bahars
paper_title: "I Want It That Way": Enabling Interactive Decision Support Using Large
    Language Models and Constraint Programming
paper_summary: A critical factor in the success of decision support systems is the accurate
  modeling of user preferences. Psychology research has demonstrated that users
  often develop their preferences during the elicitation process, highlighting
  the pivotal role of system-user interaction in developing personalized systems.
  This paper introduces a novel approach, combining Large Language Models (LLMs)
  with Constraint Programming to facilitate interactive decision support. We
  study this hybrid framework through the lens of meeting scheduling, a
  time-consuming daily activity faced by a multitude of information workers. We
  conduct three studies to evaluate the novel framework, including a diary study
  (n=64) to characterize contextual scheduling preferences, a quantitative
  evaluation of the system's performance, and a user study (n=10) with a
  prototype system. Our work highlights the potential for a hybrid LLM and
  optimization approach for iterative preference elicitation and design
  considerations for building systems that support human-system collaborative
  decision-making processes.
paper_ai_keywords: Large Language Models (LLMs) Constraint Programming Diffusion-consuming diary study contextual scheduling preferences quantitative evaluation user study iterative preference elicitation human-system collaborative decision-making processes