118 citations · 227 across the 13 of their papers we have counts for
Showing 2024 · cs.LGShow all
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cs.LG2024★ 1 cited
Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification
Shang Liu, Zhongze Cai, Guanting Chen +1
Predicting simple function classes has been widely used as a testbed for developing theory and understanding of the trained Transformer's in-context learning (ICL) ability. In this…
cs.LG2024
Understanding the Training and Generalization of Pretrained Transformer for Sequential Decision Making
Hanzhao Wang, Yu Pan, Fupeng Sun +4
In this paper, we consider the supervised pre-trained transformer for a class of sequential decision-making problems. The class of considered problems is a subset of the general fo…
cs.LG2024★ 6 cited
Uncertainty Estimation and Quantification for LLMs: A Simple Supervised Approach
Linyu Liu, Yu Pan, Xiaocheng Li +1
In this paper, we study the problem of uncertainty estimation and calibration for LLMs. We begin by formulating the uncertainty estimation problem, a relevant yet underexplored are…