papers

Publications (20)

cs.IR2022

Analysis and Optimization of GNN-Based Recommender Systems on Persistent Memory

Yuwei Hu, Jiajie Li, Zhongming Yu +1

Graph neural networks (GNNs), which have emerged as an effective method for handling machine learning tasks on graphs, bring a new approach to building recommender systems, where t…

cs.AI2025

Rethinking and Benchmarking Large Language Models for Graph Reasoning

Yuwei Hu, Xinyi Huang, Zhewei Wei +2

Large Language Models (LLMs) for Graph Reasoning have been extensively studied over the past two years, involving enabling LLMs to understand graph structures and reason on graphs…

cs.CV2021

Dense Pruning of Pointwise Convolutions in the Frequency Domain

Mark Buckler, Neil Adit, Yuwei Hu +2

Depthwise separable convolutions and frequency-domain convolutions are two recent ideas for building efficient convolutional neural networks. They are seemingly incompatible: the v…

cs.LG2019

Improving Neural Network Quantization without Retraining using Outlier Channel Splitting

Ritchie Zhao, Yuwei Hu, Jordan Dotzel +2

Quantization can improve the execution latency and energy efficiency of neural networks on both commodity GPUs and specialized accelerators. The majority of existing literature foc…

cs.GT2026

Robust Information Design with Heterogeneous Beliefs in Bayesian Congestion Games

Yuwei Hu, Bryce L. Ferguson

In many engineered systems, agents make decisions under incomplete information, creating opportunities for a planner to influence decentralized behavior through signaling. We study…

cs.AI2025

Scalable and Accurate Graph Reasoning with LLM-based Multi-Agents

Yuwei Hu, Runlin Lei, Xinyi Huang +2

Recent research has explored the use of Large Language Models (LLMs) for tackling complex graph reasoning tasks. However, due to the intricacies of graph structures and the inheren…