# Coherence Modeling of Asynchronous Conversations: A Neural Entity Grid Approach

arXiv: https://arxiv.org/abs/1805.02275 · HTML: https://mlsanity.com/paper/1805.02275/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 May 2018.

## Built on by (most cited first, 14 of 14)

- [What's in a Summary? Laying the Groundwork for Advances in Hospital-Course Summarization](https://mlsanity.com/paper/2105.00816/) (2021)
- [SNaC: Coherence Error Detection for Narrative Summarization](https://mlsanity.com/paper/2205.09641/) (2022)
- [Can Transformer Models Measure Coherence In Text? Re-Thinking the Shuffle Test](https://mlsanity.com/paper/2107.03448/) (2021)
- [Rethinking Self-Supervision Objectives for Generalizable Coherence Modeling](https://mlsanity.com/paper/2110.07198/) (2021)
- [MAWSEO: Adversarial Wiki Search Poisoning for Illicit Online Promotion](https://mlsanity.com/paper/2304.11300/) (2023)
- [Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings](https://mlsanity.com/paper/2110.06446/) (2021)
- [Modeling Structural Similarities between Documents for Coherence Assessment with Graph Convolutional Networks](https://mlsanity.com/paper/2306.06472/) (2023)
- [A Novel Computational and Modeling Foundation for Automatic Coherence Assessment](https://mlsanity.com/paper/2310.00598/) (2023)
- [BBScore: A Brownian Bridge Based Metric for Assessing Text Coherence](https://mlsanity.com/paper/2312.16893/) (2023)
- [Transformer Models for Text Coherence Assessment](https://mlsanity.com/paper/2109.02176/) (2021)
- [Joint Modeling of Entities and Discourse Relations for Coherence Assessment](https://mlsanity.com/paper/2509.04182/) (2025)
- [Enhancing Coherence of Extractive Summarization with Multitask Learning](https://mlsanity.com/paper/2305.12851/) (2023)
- [BBScoreV2: Learning Time-Evolution and Latent Alignment from Stochastic Representation](https://mlsanity.com/paper/2405.17764/) (2024)
- [Skeleton-based Coherence Modeling in Narratives](https://mlsanity.com/paper/2604.02451/) (2026)

## Abstract (arXiv)

We propose a novel coherence model for written asynchronous conversations (e.g., forums, emails), and show its applications in coherence assessment and thread reconstruction tasks. We conduct our research in two steps. First, we propose improvements to the recently proposed neural entity grid model by lexicalizing its entity transitions. Then, we extend the model to asynchronous conversations by incorporating the underlying conversational structure in the entity grid representation and feature computation. Our model achieves state of the art results on standard coherence assessment tasks in monologue and conversations outperforming existing models. We also demonstrate its effectiveness in reconstructing thread structures.