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cs.CL2026
Robust Uncertainty Quantification for Factual Generation of Large Language Models
Yuhao Zhang, Zhongliang Yang, Linna Zhou
The rapid advancement of large language model(LLM) technology has facilitated its integration into various domains of professional and daily life. However, the persistent challenge…
cs.CL2025
LLM as Attention-Informed NTM and Topic Modeling as long-input Generation: Interpretability and long-Context Capability
Xuan Xu, Zhongliang Yang, Haolun Li +5
Topic modeling aims to produce interpretable topic representations and topic--document correspondences from corpora, but classical neural topic models (NTMs) remain constrained by…
cs.CL2024
Label-Confidence-Aware Uncertainty Estimation in Natural Language Generation
Qinhong Lin, Linna Zhou, Zhongliang Yang +1
Large Language Models (LLMs) display formidable capabilities in generative tasks but also pose potential risks due to their tendency to generate hallucinatory responses. Uncertaint…