Recently, there has been a growing interest in designing text generation systems from a
discourse coherence perspective, eg, modeling the interdependence between sentences …

We propose a local coherence model that captures the flow of what semantically connects
adjacent sentences in a text. We represent the semantics of a sentence by a vector and …

We present a multiattentive recurrent neural network architecture for automatic multilingual
readability assessment. This architecture considers raw words as its main input, but …

To date there has been very little work on assessing discourse coherence methods on real-
world data. To address this, we present a new corpus of real-world texts (GCDC) as well as …

While pretrained language models (LMs) have driven impressive gains over morpho-
syntactic and semantic tasks, their ability to model discourse and pragmatic phenomena is …

Coherence is an important aspect of text quality, and various approaches have been applied
to coherence modeling. However, existing methods solely focus on a single document's …

This work lays the foundation for automated assessments of narrative quality in student
writing. We first manually score essays for narrative-relevant traits and sub-traits, and …

Despite the recent advances in coherence modelling, most such models including state-of-
the-art neural ones, are evaluated on either contrived proxy tasks such as the standard order …

Automatically evaluating the coherence of summaries is of great significance both to enable
cost-efficient summarizer evaluation and as a tool for improving coherence by selecting high …

Entity grids and entity graphs are two frameworks for modeling local coherence. These
frameworks represent entity relations between sentences and then extract features from …