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cs.AI2026
Localizing Input Uncertainty Quantification for Large Language Models via Shapley Values
Seongjun Lee, Suwan Yoon, Changhee Lee
As large language models (LLMs) are increasingly integrated into high-stakes decision-making, the ability to reliably quantify uncertainty has become a critical requirement for saf…
cs.AI2026
Citation-Closure Retrieval and Per-Rule Attribution for Real-World Regulatory Compliance Question Answering
Yeong-Joon Ju, Seong-Whan Lee
Deploying Large Language Models (LLMs) for regulatory compliance demands rigorous traceability via comprehensive citations across multi-tiered authority structures. Unlike traditio…