Tag
This paper introduces retrieved-span training for efficient query-focused meeting summarization on the QMSum dataset, showing that fine-tuning on retrieved spans recovers performance loss and that a smaller 406M model can achieve comparable results to larger models using automatic metrics.
This paper proposes an evidence-based model to automatically generate query keywords from query-free summarization datasets, enabling the creation of query-focused summarization datasets. Experimental results show that summaries generated using evidence-based queries achieve competitive ROUGE scores compared to original queries.