The occurrence of unknown words in texts significantly hinders reading comprehension. To
improve accessibility for specific target populations, computational modeling has been …

This paper presents the results and main findings of SemEval-2021 Task 1-Lexical
Complexity Prediction. We provided participants with an augmented version of the CompLex …

We report the findings of the second Complex Word Identification (CWI) shared task
organized as part of the BEA workshop co-located with NAACL-HLT'2018. The second CWI …

Lexical simplification (LS) aims at replacing complex words with simpler alternatives. LS
commonly consists of three main steps: complex word identification, substitute generation …

State-of-the-art chatbots for English are now able to hold conversations on virtually any topic
(eg Adiwardana et al., 2020; Roller et al., 2021). However, existing dialogue systems in the …

Abstract Complex Word Identification (CWI) is concerned with detection of words in need of
simplification and is a crucial first step in a simplification pipeline. It has been shown that …

In this work, we present a novel approach to lexical complexity prediction (LCP) that
combines diverse linguistic features with encodings from deep neural networks. We explore …

Lexical complexity plays an important role in reading comprehension. lexical complexity
prediction (LCP) can not only be used as a part of Lexical Simplification systems, but also as …

This paper presents a novel architecture for recursive context-aware lexical simplification,
REC-LS, that is capable of (1) making use of the wider context when detecting the words in …

Lexical Simplification (LS) aims to simplify text at the lexical level. Existing methods rely
heavily on annotated data, making it challenging to apply in low-resource scenarios. In this …