Corpus ID: 47015717

A Simple Method for Commonsense Reasoning

  title={A Simple Method for Commonsense Reasoning},
  author={Trieu H. Trinh and Quoc V. Le},
  • Trieu H. Trinh, Quoc V. Le
  • Published 2018
  • Computer Science
  • ArXiv
  • Commonsense reasoning is a long-standing challenge for deep learning. [...] Key Method Key to our method is the use of language models, trained on a massive amount of unlabled data, to score multiple choice questions posed by commonsense reasoning tests. On both Pronoun Disambiguation and Winograd Schema challenges, our models outperform previous state-of-the-art methods by a large margin, without using expensive annotated knowledge bases or hand-engineered features.Expand Abstract
    Language Models are Unsupervised Multitask Learners
    • 1,724
    • Highly Influenced
    • Open Access
    RoBERTa: A Robustly Optimized BERT Pretraining Approach
    • 1,379
    • Open Access
    Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
    • 477
    • Open Access
    Language Models are Few-Shot Learners
    • 208
    • Open Access
    Explain Yourself! Leveraging Language Models for Commonsense Reasoning
    • 59
    • Open Access
    CTRL: A Conditional Transformer Language Model for Controllable Generation
    • 133
    • Open Access


    Publications referenced by this paper.
    Deep Residual Learning for Image Recognition
    • 49,721
    • Open Access
    Sequence to Sequence Learning with Neural Networks
    • 10,442
    • Open Access
    ImageNet classification with deep convolutional neural networks
    • 51,802
    • Open Access
    ImageNet Classification with Deep Convolutional Neural Networks
    • 51,802
    • Open Access
    Distributed Representations of Words and Phrases and their Compositionality
    • 18,700
    • Open Access
    Long Short-Term Memory
    • 30,522
    • Highly Influential
    • Open Access
    Attention is All you Need
    • 11,470
    • Highly Influential
    • Open Access
    Very Deep Convolutional Networks for Large-Scale Image Recognition
    • 39,022
    • Open Access
    Efficient Estimation of Word Representations in Vector Space
    • 14,980
    • Open Access
    Neural Machine Translation by Jointly Learning to Align and Translate
    • 12,766
    • Open Access