👤 Speaker : Matthew Shardlow
💬 Titre : Operations based Text Simplification
Abstract : In this talk, we will look at recent research on text simplification using techniques from Natural Language Processing and Generative AI. We will consider the types of linguistic operations that can be performed with a text to make it easier to read for an end user. We will also consider how current trends in research on text simplification are progressing to enable better evaluation and automated methodologies for making texts easier to read by considering the operations necessary to simplify them. The talk will cover Dr. Shardlow’s research on text simplification over the past 10 years and will also draw on recent related research from the NLP domain.
Bio : Dr. Matthew Shardlow is a Reader in Natural Language Processing in the Department of Computing and Mathematics at the Manchester Metropolitan University. He was previously a member of the National Centre for Text Mining working on a Horizon 2020 funded project and studied his PhD at the University of Manchester under an EPSRC funded centre for doctoral training. He currently leads projects with industry partners including international publicly traded companies, charities and local government. He is an organiser of the Text Simplification, Accessibility and Readability workshop (EMNLP 2022, RANLP 2023, EMNLP 2024, EMNLP 2025), the SemEval-2021 shared task on Lexical Complexity Prediction (ACL 2021), The TSAR-2022 shared task on lexical simplification (EMNLP2022) and the BEA-2024 MLSP shared task (NAACL 2024). His research interests lie in the field of natural language processing and more recently generative AI. He has previously worked on topics including named entity recognition, event extraction, machine translation, emoji semantics, text generation and has more recently explored phenomena of consciousness and anthropomorphisation in association to LLMs.
📅 Date : 06/03/2026
📍 Local : UCLouvain Faculty of Law and Criminology (More 70) ( Google Map link )