# Co-Attention Based Neural Network for Source-Dependent Essay Scoring

## TL;DR

This paper introduces a co-attention neural network for source-dependent essay scoring, improving accuracy and aligning well with expert judgments across multiple datasets.

## Contribution

It proposes a novel co-attention mechanism for better importance learning in source-dependent essay scoring models.

## Key findings

- Outperforms baseline models on two datasets
- Provides reliable score predictions
- Attention aligns with expert opinions

## Abstract

This paper presents an investigation of using a co-attention based neural network for source-dependent essay scoring. We use a co-attention mechanism to help the model learn the importance of each part of the essay more accurately. Also, this paper shows that the co-attention based neural network model provides reliable score prediction of source-dependent responses. We evaluate our model on two source-dependent response corpora. Results show that our model outperforms the baseline on both corpora. We also show that the attention of the model is similar to the expert opinions with examples.