# Deep learning evaluation using deep linguistic processing

arXiv: https://arxiv.org/abs/1706.01322 · HTML: https://mlsanity.com/paper/1706.01322/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Jun 2017.

## Built on by (most cited first, 1 of 1)

- [Visual Spatial Reasoning](https://mlsanity.com/paper/2205.00363/) (2022)

## Abstract (arXiv)

We discuss problems with the standard approaches to evaluation for tasks like visual question answering, and argue that artificial data can be used to address these as a complement to current practice. We demonstrate that with the help of existing 'deep' linguistic processing technology we are able to create challenging abstract datasets, which enable us to investigate the language understanding abilities of multimodal deep learning models in detail, as compared to a single performance value on a static and monolithic dataset.