Commonsense Causal Reasoning

4 papers with code • 0 benchmarks • 0 datasets

"Commonsense Causal Reasoning is the process of capturing and understanding the causal dependencies amongst events and actions." Luo, Zhiyi, et al. "Commonsense causal reasoning between short texts." Fifteenth International Conference on the Principles of Knowledge Representation and Reasoning. 2016.

Most implemented papers

Doing Good or Doing Right? Exploring the Weakness of Commonsense Causal Reasoning Models

badbadcode/weakCOPA ACL 2021

We mitigate this problem by simply adding a regularization loss and experimental results show that this solution not only improves the model's generalization ability, but also assists the models to perform more robustly on a challenging dataset, BCOPA-CE, which has unbiased token distribution and is more difficult for models to distinguish cause and effect.

HeadlineCause: A Dataset of News Headlines for Detecting Causalities

ilyagusev/headlinecause 28 Aug 2021

In this work, we present HeadlineCause, a dataset for detecting implicit causal relations between pairs of news headlines.

Knowledge-Augmented Language Models for Cause-Effect Relation Classification

phosseini/causal-reasoning CSRR (ACL) 2022

Previous studies have shown the efficacy of knowledge augmentation methods in pretrained language models.