Evaluating LLM Style Transfer Through Readability-Based Age Assessments
Maria Di Maro, Antonio Origlia, Leonilda Bilo, Roberta Meo, Pietro Maturi, Francesca Nappo
Correct Metadata for
Abstract
Adaptability to the audience is an important feature for conversational systems, especially in the healthcare dissemination field, where scientific concepts have to be delivered to a potentially wide range of users. This work presents an evaluation of the capability of LLMs to support style transfer according to the target user’s age group. Two complementary evaluation methods were employed: an automatic assessment based on the ARI readability index, and a human experts evaluation focusing on appropriateness depending on the user’s educational level as well as content accuracy. Results show that LLMs efficiently switch style when provided with information about the user’s age while managing content still requires the adoption of safety measures.- Anthology ID:
- 2026.iwsds-1.31
- Volume:
- Proceedings of the 16th International Workshop on Spoken Dialogue System Technology
- Month:
- February
- Year:
- 2026
- Address:
- Trento, Italy
- Editors:
- Giuseppe Riccardi, Seyed Mahed Mousavi, Maria Ines Torres, Koichiro Yoshino, Zoraida Callejas, Shammur Absar Chowdhury, Yun-Nung Chen, Frederic Bechet, Joakim Gustafson, Géraldine Damnati, Alex Papangelis, Luis Fernando D’Haro, John Mendonça, Raffaella Bernardi, Dilek Hakkani-Tur, Giuseppe "Pino" Di Fabbrizio, Tatsuya Kawahara, Firoj Alam, Gokhan Tur, Michael Johnston
- Venue:
- IWSDS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 307–311
- Language:
- URL:
- https://aclanthology.org/2026.iwsds-1.31/
- DOI:
- Bibkey:
- Cite (ACL):
- Maria Di Maro, Antonio Origlia, Leonilda Bilo, Roberta Meo, Pietro Maturi, and Francesca Nappo. 2026. Evaluating LLM Style Transfer Through Readability-Based Age Assessments. In Proceedings of the 16th International Workshop on Spoken Dialogue System Technology, pages 307–311, Trento, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Evaluating LLM Style Transfer Through Readability-Based Age Assessments (Di Maro et al., IWSDS 2026)
- Copy Citation:
- PDF:
- https://aclanthology.org/2026.iwsds-1.31.pdf
Export citation
@inproceedings{di-maro-etal-2026-evaluating,
title = "Evaluating {LLM} Style Transfer Through Readability-Based Age Assessments",
author = "Di Maro, Maria and
Origlia, Antonio and
Bilo, Leonilda and
Meo, Roberta and
Maturi, Pietro and
Nappo, Francesca",
editor = "Riccardi, Giuseppe and
Mousavi, Seyed Mahed and
Torres, Maria Ines and
Yoshino, Koichiro and
Callejas, Zoraida and
Chowdhury, Shammur Absar and
Chen, Yun-Nung and
Bechet, Frederic and
Gustafson, Joakim and
Damnati, G{\'e}raldine and
Papangelis, Alex and
D{'}Haro, Luis Fernando and
Mendon{\c{c}}a, John and
Bernardi, Raffaella and
Hakkani-Tur, Dilek and
Di Fabbrizio, Giuseppe {''}Pino{''} and
Kawahara, Tatsuya and
Alam, Firoj and
Tur, Gokhan and
Johnston, Michael",
booktitle = "Proceedings of the 16th International Workshop on Spoken Dialogue System Technology",
month = feb,
year = "2026",
address = "Trento, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.iwsds-1.31/",
pages = "307--311",
abstract = "Adaptability to the audience is an important feature for conversational systems, especially in the healthcare dissemination field, where scientific concepts have to be delivered to a potentially wide range of users. This work presents an evaluation of the capability of {LLM}s to support style transfer according to the target user{'}s age group. Two complementary evaluation methods were employed: an automatic assessment based on the {ARI} readability index, and a human experts evaluation focusing on appropriateness depending on the user{'}s educational level as well as content accuracy. Results show that {LLM}s efficiently switch style when provided with information about the user{'}s age while managing content still requires the adoption of safety measures."
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%0 Conference Proceedings %T Evaluating LLM Style Transfer Through Readability-Based Age Assessments %A Di Maro, Maria %A Origlia, Antonio %A Bilo, Leonilda %A Meo, Roberta %A Maturi, Pietro %A Nappo, Francesca %Y Riccardi, Giuseppe %Y Mousavi, Seyed Mahed %Y Torres, Maria Ines %Y Yoshino, Koichiro %Y Callejas, Zoraida %Y Chowdhury, Shammur Absar %Y Chen, Yun-Nung %Y Bechet, Frederic %Y Gustafson, Joakim %Y Damnati, Géraldine %Y Papangelis, Alex %Y D’Haro, Luis Fernando %Y Mendonça, John %Y Bernardi, Raffaella %Y Hakkani-Tur, Dilek %Y Di Fabbrizio, Giuseppe ”Pino” %Y Kawahara, Tatsuya %Y Alam, Firoj %Y Tur, Gokhan %Y Johnston, Michael %S Proceedings of the 16th International Workshop on Spoken Dialogue System Technology %D 2026 %8 February %I Association for Computational Linguistics %C Trento, Italy %F di-maro-etal-2026-evaluating %X Adaptability to the audience is an important feature for conversational systems, especially in the healthcare dissemination field, where scientific concepts have to be delivered to a potentially wide range of users. This work presents an evaluation of the capability of LLMs to support style transfer according to the target user’s age group. Two complementary evaluation methods were employed: an automatic assessment based on the ARI readability index, and a human experts evaluation focusing on appropriateness depending on the user’s educational level as well as content accuracy. Results show that LLMs efficiently switch style when provided with information about the user’s age while managing content still requires the adoption of safety measures. %U https://aclanthology.org/2026.iwsds-1.31/ %P 307-311
Markdown (Informal)
[Evaluating LLM Style Transfer Through Readability-Based Age Assessments](https://aclanthology.org/2026.iwsds-1.31/) (Di Maro et al., IWSDS 2026)
- Evaluating LLM Style Transfer Through Readability-Based Age Assessments (Di Maro et al., IWSDS 2026)
ACL
- Maria Di Maro, Antonio Origlia, Leonilda Bilo, Roberta Meo, Pietro Maturi, and Francesca Nappo. 2026. Evaluating LLM Style Transfer Through Readability-Based Age Assessments. In Proceedings of the 16th International Workshop on Spoken Dialogue System Technology, pages 307–311, Trento, Italy. Association for Computational Linguistics.