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Found 5 papers, 3 papers with code
Opening up Minds with Argumentative Dialogues
We show that while both models perform closely in terms of opening up minds, the argument-based model is significantly better on other dialogue properties such as engagement and clarity.
Analyzing Neural Discourse Coherence Models
In this work, we systematically investigate how well current models of coherence can capture aspects of text implicated in discourse organisation.
Multi-Task Learning for Coherence Modeling
We address the task of assessing discourse coherence, an aspect of text quality that is essential for many NLP tasks, such as summarization and language assessment.
Neural Automated Essay Scoring and Coherence Modeling for Adversarially Crafted Input
We demonstrate that current state-of-the-art approaches to Automated Essay Scoring (AES) are not well-suited to capturing adversarially crafted input of grammatical but incoherent sequences of sentences.
An Error-Oriented Approach to Word Embedding Pre-Training
Additionally, extending the model with corrections provides further performance gains when data sparsity is an issue.
