Papers by Jennifer Chu-Carroll
GLUCOSE: GeneraLized and COntextualized Story Explanations (2020.emnlp-main)
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Nasrin Mostafazadeh, Aditya Kalyanpur, Lori Moon, David Buchanan, Lauren Berkowitz, Or Biran, Jennifer Chu-Carroll
| Challenge: | Existing knowledge resources and pretrained language models do not include or readily predict GLUCOSE’s rich inferential content. |
| Approach: | They propose a platform for crowdsourcing GLUCOSE data at scale that uses semi-structured templates to elicit causal explanations. |
| Outcome: | The proposed model can be trained on human-readable stories and build similar models on unseen stories. |
To Test Machine Comprehension, Start by Defining Comprehension (2020.acl-main)
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| Challenge: | Existing approaches to machine reading comprehension do not adequately define comprehension, authors argue . authors argue that existing systems are not up to the task of narrative understanding as they define it . |
| Approach: | They propose a detailed definition of comprehension for short narratives . they argue existing systems are not up to the task of narrative understanding . |
| Outcome: | The proposed task definitions suggest existing systems are not up to the task of narrative understanding as they define it. |