2 papers
cs.CL2026
Semantic Uncertainty Quantification of Hallucinations in LLMs: A Quantum Tensor Network Based Method
Pragatheeswaran Vipulanandan, Kamal Premaratne, Dilip Sarkar
Large language models (LLMs) exhibit strong generative capabilities but remain vulnerable to confabulations, fluent yet unreliable outputs that vary arbitrarily even under identica…
cs.LG2025
A Quantum Tensor Network-Based Viewpoint for Modeling and Analysis of Time Series Data
Pragatheeswaran Vipulananthan, Kamal Premaratne, Dilip Sarkar +1
Accurate uncertainty quantification is a critical challenge in machine learning. While neural networks are highly versatile and capable of learning complex patterns, they often lac…