DiscoSense: Commonsense Reasoning with Discourse Connectives

22 Oct 2022  ·  Prajjwal Bhargava, Vincent Ng ·

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.

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Datasets


Introduced in the Paper:

DiscoSense

Used in the Paper:

HellaSwag test PIQA

Results from the Paper


Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Sentence Completion HellaSwag ELECTRA-Large 335M (fine-tuned on DiscoSense and HellaSwag) Accuracy 91.5 # 8
Sentence Completion HellaSwag ELECTRA-Large 335M (fine-tuned on HellaSwag) Accuracy 86.9 # 13

Methods


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