Papers › DiscoSense: Commonsense Reasoning with Discourse Connectives
DiscoSense: Commonsense Reasoning with Discourse Connectives
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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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Sentence Completion | HellaSwag | ELECTRA-Large 335M (fine-tuned on DiscoSense and HellaSwag) | Accuracy | 91.5 | #12 of 89 | Archive leaderboard | report |
| Sentence Completion | HellaSwag | ELECTRA-Large 335M (fine-tuned on HellaSwag) | Accuracy | 86.9 | #17 of 89 | Archive leaderboard | report |
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