3 papers
cs.IR2026
Doctor-RAG: A Failure-Aware Repair Framework for Agentic Retrieval-Augmented Generation
Shuguang Jiao, Chengkai Huang, Shuhan Qi +6
Agentic Retrieval-Augmented Generation interleaves retrieval and reasoning for multi-hop QA and complex knowledge tasks. As reasoning trajectories lengthen, failures become more fr…
cs.AI2024
KnobTree: Intelligent Database Parameter Configuration via Explainable Reinforcement Learning
Jiahan Chen, Shuhan Qi, Yifan Li +4
Databases are fundamental to contemporary information systems, yet traditional rule-based configuration methods struggle to manage the complexity of real-world applications with hu…
cs.LG2020
RLCFR: Minimize Counterfactual Regret by Deep Reinforcement Learning
Huale Li, Xuan Wang, Fengwei Jia +4
Counterfactual regret minimization (CFR) is a popular method to deal with decision-making problems of two-player zero-sum games with imperfect information. Unlike existing studies…