Largely due to technological advances, methods for analyzing readability have increased
significantly in recent years. While past researchers designed hundreds of formulas to …

This article proposes a novel framework for representing and measuring local coherence.
Central to this approach is the entity-grid representation of discourse, which captures …

From advertisers and marketers to salespeople and leaders, everyone wants to hold
attention. They want to make ads, pitches, presentations, and content that captivates …

We present a set of novel neural supervised and unsupervised approaches for determining
the readability of documents. In the unsupervised setting, we leverage neural language …

Instruction tuning plays a critical role in aligning large language models (LLMs) with human
preference. Despite the vast amount of open instruction datasets, naively training a LLM on …

In this paper, we consider sentence simplification as a special form of translation with the
complex sentence as the source and the simple sentence as the target. We propose a Tree …

We combine lexical, syntactic, and discourse features to produce a highly predictive model
of human readers' judgments of text readability. This is the first study to take into account …

Assessing text readability is a time-honored problem that has even more relevance in
today's information-rich world. This article provides background on how readability of texts is …

This paper introduces the CommonLit Ease of Readability (CLEAR) corpus, which provides
unique readability scores for~ 5000 text excerpts along with information about the excerpt's …

We report two essential improvements in readability assessment: 1. three novel features in
advanced semantics and 2. the timely evidence that traditional ML models (eg Random …