AI RESEARCH
Learning to Control Summaries with Score Ranking
arXiv CS.CL
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ArXi:2604.17197v1 Announce Type: new Recent advances in summarization research focus on improving summary quality across multiple criteria, such as completeness, conciseness, and faithfulness, by jointly optimizing these dimensions. However, these efforts largely overlook the challenge of controlling summary generation with respect to individual criteria, especially in the presence of their inherent trade-offs. For example, enhancing conciseness can compromise completeness, and vice versa.