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Beyond Language: Learning Commonsense from Images for Reasoning
AbstractThis paper proposes a novel approach to learn commonsense from images, instead of limited raw texts or costly constructed knowledge bases, for the commonsense reasoning problem in NLP. Our motivation …...
Explanations for CommonsenseQA: New Dataset and Models
AbstractCommonsenseQA (CQA) (Talmor et al., 2019) dataset was recently released to advance the research on common-sense question answering (QA) task. Whereas the prior work has mostly focused on proposing QA …...
Relation-aware Bidirectional Path Reasoning for Commonsense Question Answering
AbstractCommonsense Question Answering is an important natural language processing (NLP) task that aims to predict the correct answer to a question through commonsense reasoning. Previous studies utilize pre-trained models on …...
CORN: Co-Reasoning Network for Commonsense Question Answering
AbstractCommonsense question answering (QA) requires machines to utilize the QA content and external commonsense knowledge graph (KG) for reasoning when answering questions. Existing work uses two independent modules to model …...
Dynamic Relevance Graph Network for Knowledge-Aware Question Answering
AbstractThis work investigates the challenge of learning and reasoning for Commonsense Question Answering given an external source of knowledge in the form of a knowledge graph (KG). We propose a …...
Faithful Knowledge Graph Explanations in Commonsense Question Answering
AbstractKnowledge graphs are commonly used as sources of information in commonsense question answering, and can also be used to express explanations for the model’s answer choice. A common way of …...
Two is Better than Many? Binary Classification as an Effective Approach to Multi-Choice Question Answering
AbstractWe propose a simple refactoring of multi-choice question answering (MCQA) tasks as a series of binary classifications. The MCQA task is generally performed by scoring each (question, answer) pair normalized …...
Knowledgeable Parameter Efficient Tuning Network for Commonsense Question Answering
AbstractCommonsense question answering is important for making decisions about everyday matters. Although existing commonsense question answering works based on fully fine-tuned PLMs have achieved promising results, they suffer from prohibitive …...