Ruofan Wu

Long N-step Surrogate Stage Reward to Reduce Variances of Deep Reinforcement Learning in Complex Problems

2022 · arXiv (Cornell University)

High variances in reinforcement learning have shown impeding successful convergence and hurting task performance. As reward signal plays an important role in learning behavior, multi-step methods have been considered to mitigate the problem, and are …

DEDGAT: Dual Embedding of Directed Graph Attention Networks for Detecting Financial Risk

2023 · arXiv (Cornell University)

Graph representation plays an important role in the field of financial risk control, where the relationship among users can be constructed in a graph manner. In practical scenarios, the relationships between nodes in risk control …

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering

2025 · arXiv (Cornell University)

Retrieval-Augmented Generation (RAG) systems are increasingly diverse, yet many suffer from monolithic designs that tightly couple core functions like query reformulation, retrieval, reasoning, and verification. This limits their interpretability, systematic evaluation, and targeted improvement, especially …