# Narrative Modeling with Memory Chains and Semantic Supervision

arXiv: https://arxiv.org/abs/1805.06122 · HTML: https://mlsanity.com/paper/1805.06122/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 May 2018.

## Built on by (most cited first, 2 of 2)

- [Discourse Probing of Pretrained Language Models](https://mlsanity.com/paper/2104.05882/) (2021)
- [CURIE: An Iterative Querying Approach for Reasoning About Situations](https://mlsanity.com/paper/2104.00814/) (2021)

## Abstract (arXiv)

Story comprehension requires a deep semantic understanding of the narrative, making it a challenging task. Inspired by previous studies on ROC Story Cloze Test, we propose a novel method, tracking various semantic aspects with external neural memory chains while encouraging each to focus on a particular semantic aspect. Evaluated on the task of story ending prediction, our model demonstrates superior performance to a collection of competitive baselines, setting a new state of the art.