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Found 5 papers, 1 papers with code
Incorporating Graph Attention Mechanism into Geometric Problem Solving Based on Deep Reinforcement Learning
However, adding auxiliary components automatically is challenging due to the complexity in selecting suitable auxiliary components especially when pivotal decisions have to be made.
Hierarchical Aspect-guided Explanation Generation for Explainable Recommendation
In this paper, we propose a novel explanation generation framework, named Hierarchical Aspect-guided explanation Generation (HAG), for explainable recommendation.
Commonsense knowledge adversarial dataset that challenges ELECTRA
To investigate machine comprehension models' ability in handling the commonsense knowledge, we created a Question and Answer Dataset with common knowledge of Synonyms (QADS).
Commonsense Knowledge + BERT for Level 2 Reading Comprehension Ability Test
In this research, we propose a system which aims to allow computers to read articles and answer related questions with commonsense knowledge like a human being for CAT level 2.
Reading Comprehension Ability Test-A Turing Test for Reading Comprehension
In order to be able to compare the difference between people reading and machines reading, we proposed a test called (reading) Comprehension Ability Test (CAT). CAT is similar to Turing test, passing of which means we cannot differentiate people from algorithms in term of their comprehension ability.
