long-text

LoomSum is a training-free framework that improves faithful summarization of long text-table documents by explicitly linking quantitative facts with narrative evidence, and introduces a new metric TGF for evaluating faithfulness.

The paper introduces MIL-BERT, an algorithm for classifying arbitrarily long texts by selecting relevant excerpts, achieving state-of-the-art results on multiple datasets with performance and explanatory guarantees.