11 papers
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…
MUSE-Autoskill: Self-Evolving Agents via Skill Creation, Memory, Management, and Evaluation
Huawei Lin, Peng Li, Jie Song +2
Large language model (LLM) agents rely on reusable skills to solve complex tasks, but existing skill creation approaches often treat skills as isolated, static artifacts, limiting…
Epistemic Gain, Aleatoric Cost: Uncertainty Decomposition in Multi-Agent Debate for Math Reasoning
Dan Qiao, Binbin Chen, Fengyu Cai +7
Multi-Agent Debate (MAD) has shown promise in improving reasoning and reducing hallucinations, yet it remains unclear how information exchange shapes individual reasoning behavior.…
Reasoning and Tool-use Compete in Agentic RL:From Quantifying Interference to Disentangled Tuning
Yu Li, Mingyang Yi, Xiuyu Li +6
Agentic Reinforcement Learning (ARL) trains large language models to interleave reasoning with external tool execution to solve complex tasks. Most existing ARL methods train a sin…
Can Large Language Models be a Cardinality Estimator? An Empirical study
Liangzu Liu, Yiyan Wang, Yinjun Wu +8
Cardinality estimation (CardEst) still remains a challenging problem for DBMS. Recent years have witnessed the success of ML-based cardinality estimators in outperforming tradition…
Disentangled Parameter-Efficient Linear Model for Long-Term Time Series Forecasting
Yuang Zhao, Tianyu Li, Jiadong Chen +3
Long-term Time Series Forecasting (LTSF) is crucial across various domains, but complex deep models like Transformers are often prone to overfitting on extended sequences. Linear F…