Utilizing Silver Standard Data for Enhanced Zero-shot Classification in Information Extraction

The author proposes the Clean-LaVe framework to leverage silver standard data for improved zero-shot classification performance by detecting clean data and finetuning pre-trained models. The approach involves Iteratively Weighted Negative Learning and Class-Aware Data Selector to address noisy data and broaden class selection.