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As language models continue to scale, Large Language Models (LLMs) have exhibited emerging capabilities in In-Context Learning (ICL), enabling them to solve language tasks by prefixing a few in-context demonstrations (ICDs) as context. Inspired by th
Externí odkaz:
http://arxiv.org/abs/2406.13185
Autor:
Hao, Chenduo, Zhang, Xu
The Natural Language to SQL (NL2SQL) technique is used to convert natural language queries into executable SQL statements. Typically, slot-filling is employed as a classification method for multi-task cases to achieve this goal. However, slot-filling
Externí odkaz:
http://arxiv.org/abs/2306.17727
The NL2SQL task involves parsing natural language statements into SQL queries. While most state-of-the-art methods treat NL2SQL as a slot-filling task and use feature representation learning techniques, they overlook explicit correlation features bet
Externí odkaz:
http://arxiv.org/abs/2306.17646