All deadlines are 11:59PM UTC-12:00 (“anywhere on Earth”).
The organisers are pleased to present the fourth instalment of the annual workshop on Text Simplification, Accessibility and Readability (TSAR 2025), colocated with EMNLP 2025 in Suzhou, China. TSAR aims to provide a cohesive environment to draw members of the computational linguistics, natural language processing and artificial intelligence communities working on the use of automated techniques to make language accessible for all. Previous editions of the workshop have been held at EMNLP (2022, 2024) and RANLP (2023) with significant engagement and participation driving research and building community in the fields of Text Simplification, Accessibility and Readability.
Research in automatic text simplification (TS) has often focused on proposing the use of methods derived from the deep learning paradigm (Martin et al., 2020; Maddela et al., 2021; Sheang and Saggion, 2021). Recently, work in text simplification has leveraged the new era of foundational large language models through fine-tuning and prompt-engineering to produce simplifications (Kew et al. 2023; Cripwell et al. 2023; Farajidizaji et al. 2024).
However, there are many important aspects in automatic TS that require the attention of our community: the design of appropriate evaluation metrics (Štajner et al., 2022), the development of context-aware simplification solutions (Yimam et al., 2018; Shardlow et al., 2022a; Saggion et al., 2022), the creation of appropriate language resources to support research and evaluation (Maddela and Xu, 2018; Shardlow et al., 2020; Ferres and Saggion, 2022; North et al., 2022), the deployment of simplification in real environments for real users (Lee and Yeung, 2018; Alonzo et al., 2022), the study of discourse factors in text simplification (Zhong et al., 2019), the identification of factors affecting the readability of a text (Shardlow et al., 2022b), among others. To overcome those issues, there is a need for collaboration of CL/NLP researchers, machine learning and deep learning researchers, UI/UX and Accessibility professionals, as well as public organisations representatives (Štajner, 2021).
The TSAR 2024 workshop builds upon the recent success of several regional workshops that covered a subset of our topics of interest, including READI Workshops at LREC 2022 and LREC 2024, SEPLN 2021 Workshop on Current Trends in Text Simplification (CTTS)), the SimpleText workshop at CLEF 2021, as well as the birds-of-a-feather events on Text Simplification at NAACL 2021 (over 50 participants), ACL 2022, EMNLP 2023 and EMNLP 2024.
The TSAR 2025 workshop will invite contributions on the following topics, aligned with previous editions of the workshop:
We welcome three types of papers: long papers, short papers and demos.
The papers should present novel research. The review will be double blind and thus all submissions should be anonymized.
Long and Short Papers: We adhere to the same guidelines as EMNLP 2025.
Demo Papers: Demos should be six pages in length, including references, and should describe implemented systems related to the topics of interest of the workshop. It also should include a link to a short screencast of the working software. In addition, authors of demo papers must be willing to present a demo of their system during TSAR 2025. Further guidance on the preparation of demo papers is available through the main conference website.