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Found 3 papers, 1 papers with code
Towards preserving word order importance through Forced Invalidation
Large pre-trained language models such as BERT have been widely used as a framework for natural language understanding (NLU) tasks.
Numerical reasoning in machine reading comprehension tasks: are we there yet?
The current standings of these models in the DROP leaderboard, over standard metrics, suggest that the models have achieved near-human performance.
Discrete Reasoning Templates for Natural Language Understanding
Reasoning about information from multiple parts of a passage to derive an answer is an open challenge for reading-comprehension models.
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