Abstract:We study the task of long-form opinion text generation, which faces at least two distinct challenges. First, existing neural generation models fall short of coherence, thus requiring efficient content planning. Second, diverse types of information are needed to guide the generator to cover both subjective and objective content. To this end, we propose DY-PLOC, a generation framework that conducts dynamic planning of content while generating the output based on a novel design of mixed language models. To enrich… Show more
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