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This chapter will present solutions to the main challenges of Table-to-Text listed in Chapter 8 . It focuses on Deep Learning Table-to-Text architectures, which integrate various of these solutions into a unified framework. This chapter focuses specifically on Table-to-Text systems, as in a Natural Language Interface to Databases (NLIDB), the result of an executed query is typically returned in the form of a table, meaning that there is some alignment between Table-to-Text and an NLIDB

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Table-to-Text Neural Architecture and Systems

  • 章节

  • 发表日期：

    2026年

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  • George Katsogiannis-Meimarakis,
  • Anna Mitsopoulou,
  • Mike Xydas,
  • Georgia Koutrika

摘要

This chapter will present solutions to the main challenges of Table-to-Text listed in Chapter 8 . It focuses on Deep Learning Table-to-Text architectures, which integrate various of these solutions into a unified framework. This chapter focuses specifically on Table-to-Text systems, as in a Natural Language Interface to Databases (NLIDB), the result of an executed query is typically returned in the form of a table, meaning that there is some alignment between Table-to-Text and an NLIDB