3 papers
cs.CL2025
What Really Matters for Table LLMs? A Meta-Evaluation of Model and Data Effects
Naihao Deng, Sheng Zhang, Henghui Zhu +7
Table modeling has progressed for decades. In this work, we revisit this trajectory and highlight emerging challenges in the LLM era, particularly the paradox of choice: the diffic…
cs.CL2024
PRACTIQ: A Practical Conversational Text-to-SQL dataset with Ambiguous and Unanswerable Queries
Mingwen Dong, Nischal Ashok Kumar, Yiqun Hu +9
Previous text-to-SQL datasets and systems have primarily focused on user questions with clear intentions that can be answered. However, real user questions can often be ambiguous w…
cs.CL2024
You Only Read Once (YORO): Learning to Internalize Database Knowledge for Text-to-SQL
Hideo Kobayashi, Wuwei Lan, Peng Shi +5
While significant progress has been made on the text-to-SQL task, recent solutions repeatedly encode the same database schema for every question, resulting in unnecessary high infe…