# A Simple Machine Learning Method for Commonsense Reasoning? A Short Commentary on Trinh & Le (2018)

arXiv: https://arxiv.org/abs/1810.00521 · HTML: https://mlsanity.com/paper/1810.00521/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Oct 2018.

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

- [Towards Zero-shot Commonsense Reasoning with Self-supervised Refinement of Language Models](https://mlsanity.com/paper/2109.05105/) (2021)
- [Attention-based Contrastive Learning for Winograd Schemas](https://mlsanity.com/paper/2109.05108/) (2021)

## Abstract (arXiv)

This is a short Commentary on Trinh & Le (2018) ("A Simple Method for Commonsense Reasoning") that outlines three serious flaws in the cited paper and discusses why data-driven approaches cannot be considered as serious models for the commonsense reasoning needed in natural language understanding in general, and in reference resolution, in particular.