1 citations · 2 across the 3 of their papers we have counts for
5 papers
TT-SAX: A Two-Track Time Series Symbolization for Natural Language Shape Querying
Zhao Tan, Xianglong Bao, Zhipeng Xi +1
Natural language querying for time series databases aims to let users find what they need in long histories of data by asking in plain language. Shape queries ask how a series move…
LEAF-SQL: Level-wise Exploration with Adaptive Fine-graining for Text-to-SQL Skeleton Prediction
Zhao Tan, Xiping Liu, Qing Shu +3
Text-to-SQL translates natural language questions into executable SQL queries, enabling intuitive database access for non-experts. While large language models achieve strong perfor…
Sonar-TS: Search-Then-Verify Natural Language Querying for Time Series Databases
Zhao Tan, Yiji Zhao, Shiyu Wang +5
Natural Language Querying for Time Series Databases (NLQ4TSDB) aims to assist non-expert users retrieve meaningful events, intervals, and summaries from massive temporal records. H…
KeyInst: Keyword Instruction for Improving SQL Formulation in Text-to-SQL
Xiping Liu, Zhao Tan
Text-to-SQL parsing involves the translation of natural language queries (NLQs) into their corresponding SQL commands. A principal challenge within this domain is the formulation o…
EPI-SQL: Enhancing Text-to-SQL Translation with Error-Prevention Instructions
Xiping Liu, Zhao Tan
The conversion of natural language queries into SQL queries, known as Text-to-SQL, is a critical yet challenging task. This paper introduces EPI-SQL, a novel methodological framewo…