20 citations · 35 across the 9 of their papers we have counts for
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cs.IR2026
Uncertainty Quantification for LLM Agents: A Taxonomy, an Evaluation Protocol, and an Empirical Study
Moule Lin, Qizhen Lan, Shuhao Guan +4
Large language models (LLMs) are no longer deployed only for single-turn conversation but increasingly act as agents that plan, call tools, retrieve evidence, maintain memory, and…
cs.CL2026
LiveFact: A Dynamic, Time-Aware Benchmark for LLM-Driven Fake News Detection
Cheng Xu, Changhong Jin, Yingjie Niu +5
The rapid development of Large Language Models (LLMs) has transformed fake news detection and fact-checking tasks from simple classification to complex reasoning. However, evaluati…
cs.AI2026
Bayesian-LoRA: Probabilistic Low-Rank Adaptation of Large Language Models
Moule Lin, Shuhao Guan, Andrea Patane +2
Large Language Models usually put more emphasis on accuracy and therefore, will guess even when not certain about the prediction, which is especially severe when fine-tuned on smal…