activity
20242026
collaborators

13 papers

cs.DB2026

EcoTable: Cost-effective Table Integration in Data Lakes for Natural Language Queries

Yuhui Wang, Jinqi Liu, Chengliang Chai +8

The diverse formats of CSV and Parquet files in data lakes pose a significant challenge to traditional ETL, which relies on data engineers to pre-define a target database schema an…

cs.CL2026

Reward-SQL: Boosting Text-to-SQL via Stepwise Execution-Aware Reasoning and Process-Supervised Rewards

Yuxin Zhang, Meihao Fan, Ju Fan +5

Recent advances in large language models (LLMs) trained with reinforcement learning (RL) have improved Text-to-SQL performance. However, RL-based approaches still struggle with com…

cs.DB2026

Dial: A Knowledge-Grounded Dialect-Specific NL2SQL System

Xiang Zhang, Hongming Xu, Le Zhou +8

Enterprises commonly deploy heterogeneous database systems, each of which owns a distinct SQL dialect with different syntax rules, built-in functions, and execution constraints. Ho…

cs.DB2026

Data Agents: Levels, State of the Art, and Open Problems

Yuyu Luo, Guoliang Li, Ju Fan +1

Data agents are an emerging paradigm that leverages large language models (LLMs) and tool-using agents to automate data management, preparation, and analysis tasks. However, the te…

cs.DB2025

A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?

Xinyu Liu, Shuyu Shen, Boyan Li +7

Translating users' natural language queries (NL) into SQL queries (i.e., Text-to-SQL, a.k.a. NL2SQL) can significantly reduce barriers to accessing relational databases and support…

cs.CV2025

RAMer: Reconstruction-based Adversarial Model for Multi-party Multi-modal Multi-label Emotion Recognition

Xudong Yang, Yizhang Zhu, Hanfeng Liu +3

Conventional Multi-modal multi-label emotion recognition (MMER) assumes complete access to visual, textual, and acoustic modalities. However, real-world multi-party settings often…