@article{Štajner_Sheang_Saggion_2022, title={Sentence Simplification Capabilities of Transfer-Based Models}, volume={36}, url={https://ojs.aaai.org/index.php/AAAI/article/view/21477}, DOI={10.1609/aaai.v36i11.21477}, abstractNote={According to the official adult literacy report conducted in 24 highly-developed countries, more than 50% adults, on average, can only understand basic vocabulary, short sentences, and basic syntactic constructions. Everyday information found in news articles is thus inaccessible to many people, impeding their social inclusion and informed decision-making. Systems for automatic sentence simplification aim to provide scalable solution to this problem. In this paper, we propose new state-of-the-art sentence simplification systems for English and Spanish, and specifications for expert evaluation that are in accordance with well-established easy-to-read guidelines. We conduct expert evaluation of our new systems and the previous state-of-the-art systems for English and Spanish, and discuss strengths and weaknesses of each of them. Finally, we draw conclusions about the capabilities of the state-of-the-art sentence simplification systems and give some directions for future research.}, number={11}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Štajner, Sanja and Sheang, Kim Cheng and Saggion, Horacio}, year={2022}, month={Jun.}, pages={12172-12180} }