20 papers
Benchmarking Knowledge-Extraction Attack and Defense on Retrieval-Augmented Generation
Zhisheng Qi, Utkarsh Sahu, Li Ma +9
Retrieval-Augmented Generation (RAG) has become a cornerstone of knowledge-intensive applications, including enterprise chatbots, healthcare assistants, and agentic memory manageme…
DynLP: Parallel Dynamic Batch Update for Label Propagation in Semi-Supervised Learning
S M Shovan, Arindam Khanda, S M Ferdous +2
Semi-supervised learning aims to infer class labels using only a small fraction of labeled data. In graph-based semi-supervised learning, this is typically achieved through label p…
Knowledge Homophily in Large Language Models
Utkarsh Sahu, Zhisheng Qi, Mahantesh Halappanavar +6
Large Language Models (LLMs) have been increasingly studied as neural knowledge bases for supporting knowledge-intensive applications such as question answering and fact checking.…
Towards High Resolution Probabilistic Coastal Inundation Forecasting from Sparse Observations
Kazi Ashik Islam, Zakaria Mehrab, Mahantesh Halappanavar +5
Coastal flooding poses increasing threats to communities worldwide, necessitating accurate and hyper-local inundation forecasting for effective emergency response. However, real-wo…
Anonymized Network Sensing using C++26 std::execution on GPUs
Michael Mandulak, Sayan Ghosh, S M Ferdous +2
Large-scale network sensing plays a vital role in network traffic analysis and characterization. As network packet data grows increasingly large, parallel methods have become mains…
On the System Theoretic Offline Learning of Continuous-Time LQR with Exogenous Disturbances
Sayak Mukherjee, Ramij R. Hossain, Mahantesh Halappanavar
We analyze offline designs of linear quadratic regulator (LQR) strategies with uncertain disturbances. First, we consider the scenario where the exogenous variable can be estimated…