"I Want It That Way": Enabling Interactive Decision Support Using Large
  Language Models and Constraint Programming
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.
65791c3f1bf8e371c4fde7df
Connor Lawless
65791c3f1bf8e371c4fde7e0
Jakob Schoeffer
65791c3f1bf8e371c4fde7e1
Lindy Le
65791c3f1bf8e371c4fde7e2
Kael Rowan
65791c3f1bf8e371c4fde7e3
Shilad Sen
65791c3f1bf8e371c4fde7e4
Cristina St. Hill
65791c3f1bf8e371c4fde7e5
Jina Suh
admin_assigned
2023-12-13T11:00:15.150Z
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/avatars/b2b8a92d5877a0c60e890f714f6d955a.svg
Jina Suh
user
jinasuh
65791c3f1bf8e371c4fde7e6
Bahar Sarrafzadeh
claimed_verified
2023-12-14T10:34:57.023Z
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/avatars/d57162831554f95d55bae85689ad7a29.svg
Bahareh Sarrafzadeh
user
Bahars
"I Want It That Way": Enabling Interactive Decision Support Using Large
  Language Models and Constraint Programming
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.
A hybrid approach combining Large Language Models (LLMs) and Constraint Programming enhances interactive decision support systems by iteratively eliciting user preferences, demonstrated through meeting scheduling.
Large Language Models (LLMs) Constraint Programming iterative preference elicitation hybrid framework meeting scheduling user-system collaborative decision-making