@inproceedings{griol-etal-2025-trustboost,
title = "{T}rust{B}oost: Balancing flexibility and compliance in conversational {AI} systems",
author = "Griol, David and
Callejas, Zoraida and
Gil-Mart{\'i}n, Manuel and
Kharitonova, Ksenia and
Montero-Mart{\'i}nez, Juan Manuel and
P{\'e}rez Fern{\'a}ndez, David and
Fern{\'a}ndez-Mart{\'i}nez, Fernando",
editor = "Torres, Maria Ines and
Matsuda, Yuki and
Callejas, Zoraida and
del Pozo, Arantza and
D'Haro, Luis Fernando",
booktitle = "Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology",
month = may,
year = "2025",
address = "Bilbao, Spain",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.iwsds-1.16/",
pages = "172--175",
ISBN = "979-8-89176-248-0",
abstract = "Conversational AI (ConvAI) systems are gaining growing importance as an alternative for more natural interaction with digital services. In this context, Large Language Models (LLMs) have opened new possibilities for less restricted interaction and richer natural language understanding. However, despite their advanced capabilities, LLMs can pose accuracy and reliability problems, as they sometimes generate factually incorrect or contextually inappropriate content that does not fulfill the regulations or business rules of a specific application domain. In addition, they still do not possess the capability to adjust to users' needs and preferences, showing emotional awareness, while concurrently adhering to the regulations and limitations of their designated domain. In this paper we present the TrustBoost project, which addresses the challenge of improving trustworthiness of ConvAI from two dimensions: cognition (adaptability, flexibility, compliance, and performance) and affectivity (familiarity, emotional dimension, and perception). The duration of the project is from September 2024 to December 2027."
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<abstract>Conversational AI (ConvAI) systems are gaining growing importance as an alternative for more natural interaction with digital services. In this context, Large Language Models (LLMs) have opened new possibilities for less restricted interaction and richer natural language understanding. However, despite their advanced capabilities, LLMs can pose accuracy and reliability problems, as they sometimes generate factually incorrect or contextually inappropriate content that does not fulfill the regulations or business rules of a specific application domain. In addition, they still do not possess the capability to adjust to users’ needs and preferences, showing emotional awareness, while concurrently adhering to the regulations and limitations of their designated domain. In this paper we present the TrustBoost project, which addresses the challenge of improving trustworthiness of ConvAI from two dimensions: cognition (adaptability, flexibility, compliance, and performance) and affectivity (familiarity, emotional dimension, and perception). The duration of the project is from September 2024 to December 2027.</abstract>
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%0 Conference Proceedings
%T TrustBoost: Balancing flexibility and compliance in conversational AI systems
%A Griol, David
%A Callejas, Zoraida
%A Gil-Martín, Manuel
%A Kharitonova, Ksenia
%A Montero-Martínez, Juan Manuel
%A Pérez Fernández, David
%A Fernández-Martínez, Fernando
%Y Torres, Maria Ines
%Y Matsuda, Yuki
%Y Callejas, Zoraida
%Y del Pozo, Arantza
%Y D’Haro, Luis Fernando
%S Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology
%D 2025
%8 May
%I Association for Computational Linguistics
%C Bilbao, Spain
%@ 979-8-89176-248-0
%F griol-etal-2025-trustboost
%X Conversational AI (ConvAI) systems are gaining growing importance as an alternative for more natural interaction with digital services. In this context, Large Language Models (LLMs) have opened new possibilities for less restricted interaction and richer natural language understanding. However, despite their advanced capabilities, LLMs can pose accuracy and reliability problems, as they sometimes generate factually incorrect or contextually inappropriate content that does not fulfill the regulations or business rules of a specific application domain. In addition, they still do not possess the capability to adjust to users’ needs and preferences, showing emotional awareness, while concurrently adhering to the regulations and limitations of their designated domain. In this paper we present the TrustBoost project, which addresses the challenge of improving trustworthiness of ConvAI from two dimensions: cognition (adaptability, flexibility, compliance, and performance) and affectivity (familiarity, emotional dimension, and perception). The duration of the project is from September 2024 to December 2027.
%U https://aclanthology.org/2025.iwsds-1.16/
%P 172-175
Markdown (Informal)
[TrustBoost: Balancing flexibility and compliance in conversational AI systems](https://aclanthology.org/2025.iwsds-1.16/) (Griol et al., IWSDS 2025)
ACL
- David Griol, Zoraida Callejas, Manuel Gil-Martín, Ksenia Kharitonova, Juan Manuel Montero-Martínez, David Pérez Fernández, and Fernando Fernández-Martínez. 2025. TrustBoost: Balancing flexibility and compliance in conversational AI systems. In Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology, pages 172–175, Bilbao, Spain. Association for Computational Linguistics.