Generalized Entity Matching with Machop

We use Generalized Entity Matching (GEM) to satisfy these practical requirements and present an end-to-end pipeline, Machop, as the solution. Machop allows end users to define new matching tasks from scratch and apply them to new domains in a step-by-step manner. Machop casts the GEM problem as sequence pair classification so as to utilize the language understanding capability of Transformers-based language models (LMs) such as BERT.

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Minun and Explainable Entity Matching

it is important to develop a framework to explain the results of DL-based EM models. We developed Minun, a model-agnostic framework to provide local explanations for black-box EM models. Minun employs counterfactual examples of entity pairs as the explanation.

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CoCoSum: Summarizing Contrastive and Common Opinions from Reviews

In this blog post, we take one step beyond the current scope of opinion summarization and propose CoCoSum, a framework which aims to generate contrastive and common summaries by comparing multiple entities. This framework consists of two base summarization models that jointly generate contrastive and common summaries.

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