2 citations · 3 across the 14 of their papers we have counts for
4 papers · 1 filter
Selm: Self-Evolving Library Management for Multi-Skill Agent Optimization
Mengxi Hu, Yuxuan Hu, Jinbo Su +6
Large language model (LLM) agents increasingly use skills as a lightweight way to acquire task-specific knowledge. Recent work enables skills to evolve from task trajectories. Howe…
ACTS-SQL: Agentic and Critic-Oriented Tree-Structured SQL Correctness with Large Language Models
Xinmei Huang, Jie Song, Peng Li +10
Large Language Models (LLMs) have been increasingly adopted in Text-to-SQL systems, yet SQL errors remain a major obstacle in real-world Text-to-SQL inference pipelines. Existing S…
IDSTune: A Multi-Agent Collaborative Framework for Integrated Database System Tuning
Yiyan Li, Guanli Liu, Renata Borovica-Gajic +6
Database tuning is critical for achieving high performance in modern database management systems (DBMSs). Existing methods typically optimize a single component---knobs, indexes, o…
TableCache: Primary Foreign Key Guided KV Cache Precomputation for Low Latency Text-to-SQL
Jinbo Su, Yuxuan Hu, Cuiping Li +4
In Text-to-SQL tasks, existing LLM-based methods often include extensive database schemas in prompts, leading to long context lengths and increased prefilling latency. While user q…