Слабо Супервизируемая Модель

AbstractThe most common metrics for assessing summarization algorithms do not account for whether summaries are factually consistent with source documents. We propose a weakly-supervised, model-based approach for verifying factual consistency …...

We propose a new task and dataset for a common problem in social science research: “upsampling” coarse document labels to fine- grained labels or spans. We pose the problem in …...

AbstractOne desiderata of topic modeling is to produce interpretable topics. Given a cluster of document-tokens comprising a topic, we can order the topic by counting each word. It is natural …...

AbstractSolving math word problems (MWPs) is an important and challenging problem in natural language processing. Existing approaches to solving MWPs require full supervision in the form of intermediate equations. However, …...