3 citations · 7 across the 6 of their papers we have counts for
7 papers
AgenticRag-R1: Agentic Reinforcement Learning with Stack Memory for Multi-Step Reasoning, Retrieval and Memorizing
Xinke Jiang, Yue Fang, Zhibang Yang +12
Retrieval-Augmented Generation (RAG) improves the factuality of large language models (LLMs), yet existing RAG systems often struggle with complex, multi-step reasoning that requir…
Fishing Out Free Riders: Shapley-Based Reward Attribution for Parallel Reasoning via Reinforcement Learning
Wentao Zhang, Haoyu Zhang, Xinke Jiang +7
Large Language Models (LLMs) excel at multi-step reasoning, yet current parallel reasoning approaches often fail to distinguish the contributions of individual reasoning paths. Man…
STRAP: Spatio-Temporal Pattern Retrieval for Out-of-Distribution Generalization
Haoyu Zhang, Wentao Zhang, Hao Miao +3
Spatio-Temporal Graph Neural Networks (STGNNs) have emerged as a powerful tool for modeling dynamic graph-structured data across diverse domains. However, they often fail to genera…
RAGraph: A General Retrieval-Augmented Graph Learning Framework
Xinke Jiang, Rihong Qiu, Yongxin Xu +7
Graph Neural Networks (GNNs) have become essential in interpreting relational data across various domains, yet, they often struggle to generalize to unseen graph data that differs…
TC-RAG:Turing-Complete RAG's Case study on Medical LLM Systems
Xinke Jiang, Yue Fang, Rihong Qiu +10
In the pursuit of enhancing domain-specific Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) emerges as a promising solution to mitigate issues such as hallucinat…
Kuaiji: the First Chinese Accounting Large Language Model
Jiayuan Luo, Songhua Yang, Xiaoling Qiu +5
Large Language Models (LLMs) like ChatGPT and GPT-4 have demonstrated impressive proficiency in comprehending and generating natural language. However, they encounter difficulties…
Time Series Supplier Allocation via Deep Black-Litterman Model
Jiayuan Luo, Wentao Zhang, Yuchen Fang +4
Time Series Supplier Allocation (TSSA) poses a complex NP-hard challenge, aimed at refining future order dispatching strategies to satisfy order demands with maximum supply efficie…