Abstract
We present DiscoSense, a benchmark for commonsense reasoning via understanding a wide variety of discourse connectives. We generate compelling distractors in DiscoSense using Conditional Adversarial Filtering, an extension of Adversarial Filtering that employs conditional generation. We show that state-of-the-art pre-trained language models struggle to perform well on DiscoSense, which makes this dataset ideal for evaluating next-generation commonsense reasoning systems.- Anthology ID:
- 2022.emnlp-main.703
- Volume:
- Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates
- Editors:
- Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 10295–10310
- Language:
- URL:
- https://aclanthology.org/2022.emnlp-main.703
- DOI:
- 10.18653/v1/2022.emnlp-main.703
- Cite (ACL):
- Prajjwal Bhargava and Vincent Ng. 2022. DiscoSense: Commonsense Reasoning with Discourse Connectives. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 10295–10310, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
- Cite (Informal):
- DiscoSense: Commonsense Reasoning with Discourse Connectives (Bhargava & Ng, EMNLP 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.emnlp-main.703.pdf