7 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…
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)…
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 +4
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…
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…