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Sentence summarization aims at compressing a long sentence into a short onethat keeps the main gist, and has extensive real-world applications such asheadline generation. In previous work, researchers have developed variousapproaches to improve the ROUGE score, which is the main evaluation metric forsummarization, whereas controlling the summary length has not drawn muchattention. In our work, we address a new problem of explicit character-levellength control for summarization, and propose a dynamic programming algorithmbased on the Connectionist Temporal Classification (CTC) model. Results showthat our approach not only achieves higher ROUGE scores but also yields morecomplete sentences.

A Character-Level Length-Control Algorithm for Non-Autoregressive Sentence Summarization