5 citations · 7 across the 12 of their papers we have counts for
12 papers
Can LLM Agents Price Competitively? A Dynamic Multi-Attribute Auction Benchmark for Agentic Commerce
Shimaa Ahmed, Yiwei Cai, Mohsen Minaei +1
Agentic commerce is moving from concept to deployed infrastructure: payment networks, retailers, and AI platforms are setting the stage for agents to transact on behalf of merchant…
Secure and Privacy-Preserving Vertical Federated Learning
Shan Jin, Sai Rahul Rachuri, Yizhen Wang +2
We propose a novel end-to-end privacy-preserving framework, instantiated by three efficient protocols for different deployment scenarios, covering both input and output privacy, fo…
Detecting Data Poisoning in Code Generation LLMs via Black-Box, Vulnerability-Oriented Scanning
Shenao Yan, Shimaa Ahmed, Shan Jin +5
Code generation large language models (LLMs) are increasingly integrated into modern software development workflows. Recent work has shown that these models are vulnerable to backd…
Understanding LLM Evaluator Behavior: A Structured Multi-Evaluator Framework for Merchant Risk Assessment
Liang Wang, Junpeng Wang, Chin-chia Michael Yeh +6
Large Language Models (LLMs) are increasingly used as evaluators of reasoning quality, yet their reliability and bias in payments-risk settings remain poorly understood. We introdu…
ScaLoRA: Optimally Scaled Low-Rank Adaptation for Efficient High-Rank Fine-Tuning
Yilang Zhang, Xiaodong Yang, Yiwei Cai +1
As large language models (LLMs) continue to scale in size, the computational overhead has become a major bottleneck for task-specific fine-tuning. While low-rank adaptation (LoRA)…
SimAug: Enhancing Recommendation with Pretrained Language Models for Dense and Balanced Data Augmentation
Yuying Zhao, Xiaodong Yang, Huiyuan Chen +4
Deep Neural Networks (DNNs) are extensively used in collaborative filtering due to their impressive effectiveness. These systems depend on interaction data to learn user and item e…
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
Song Wang, Xiaodong Yang, Rashidul Islam +4
To deal with distribution shifts in graph data, various graph out-of-distribution (OOD) generalization techniques have been recently proposed. These methods often employ a two-step…
GAIM: Attacking Graph Neural Networks via Adversarial Influence Maximization
Xiaodong Yang, Xiaoting Li, Huiyuan Chen +1
Recent studies show that well-devised perturbations on graph structures or node features can mislead trained Graph Neural Network (GNN) models. However, these methods often overloo…
SimCE: Simplifying Cross-Entropy Loss for Collaborative Filtering
Xiaodong Yang, Huiyuan Chen, Yuchen Yan +5
The learning objective is integral to collaborative filtering systems, where the Bayesian Personalized Ranking (BPR) loss is widely used for learning informative backbones. However…
Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness
Yuying Zhao, Minghua Xu, Huiyuan Chen +5
Recommender systems (RSs) have gained widespread applications across various domains owing to the superior ability to capture users' interests. However, the complexity and nuanced…
Enhancing Transformers without Self-supervised Learning: A Loss Landscape Perspective in Sequential Recommendation
Vivian Lai, Huiyuan Chen, Chin-Chia Michael Yeh +3
Transformer and its variants are a powerful class of architectures for sequential recommendation, owing to their ability of capturing a user's dynamic interests from their past int…
Energy Efficient Obfuscation of Side-Channel Leakage for Preventing Side-Channel Attacks
Shan Jin, Minghua Xu, Yiwei Cai
Side-channel attacks (SCAs), which infer secret information (for example secret keys) by exploiting information that leaks from the implementation (such as power consumption), have…