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ProgramTab: Boosting Table Reasoning of LLMs via Programmatic Paradigm
Pei Guo, Enjie Liu, Yunzhi Tan +6
Table-based reasoning with large language models (LLMs), which requires reasoning based on natural language questions and structured tabular data, has gained widespread attention.…
DCMM-SQL: Automated Data-Centric Pipeline and Multi-Model Collaboration Training for Text-to-SQL Model
Yuanzhen Xie, Liu Ye, Jiqun Chu +5
Text-to-SQL tasks have gained attractive improvements since the release of ChatGPT. Among them, agent-based frameworks have been widely used in this field. However, the impact of d…
Solid-SQL: Enhanced Schema-linking based In-context Learning for Robust Text-to-SQL
Geling Liu, Yunzhi Tan, Ruichao Zhong +5
Recently, large language models (LLMs) have significantly improved the performance of text-to-SQL systems. Nevertheless, many state-of-the-art (SOTA) approaches have overlooked the…
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
Yuanzhen Xie, Xinzhou Jin, Tao Xie +7
In-context learning of large-language models (LLMs) has achieved remarkable success in the field of natural language processing, while extensive case studies reveal that the single…