Zobrazeno 1 - 10
of 599
pro vyhledávání: '"Li Xiaocheng"'
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 paper, we revisit the training of Transformers on linear regression t
Externí odkaz:
http://arxiv.org/abs/2405.15115
Autor:
Wang, Hanzhao, Pan, Yu, Sun, Fupeng, Liu, Shang, Talluri, Kalyan, Chen, Guanting, Li, Xiaocheng
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 formulation of reinforcement learning in that there is no transition pro
Externí odkaz:
http://arxiv.org/abs/2405.14219
Publikováno v:
Open Medicine, Vol 14, Iss 1, Pp 384-391 (2019)
This study evaluated the functions of matrix metalloproteinase 2 (MMP2) in hepatocellular carcinoma (HCC) cells and assessed the effects of MMP2 on HCC cell sensitivity to cisplatin.
Externí odkaz:
https://doaj.org/article/dc822471222843309794211cf3a79654
In this paper, we study the problem of uncertainty estimation and calibration for LLMs. We first formulate the uncertainty estimation problem for LLMs and then propose a supervised approach that takes advantage of the labeled datasets and estimates t
Externí odkaz:
http://arxiv.org/abs/2404.15993
In this paper, we study the problem of watermarking large language models (LLMs). We consider the trade-off between model distortion and detection ability and formulate it as a constrained optimization problem based on the green-red algorithm of Kirc
Externí odkaz:
http://arxiv.org/abs/2403.13027
Effects of environmental variables on seedling distribution of rare and endangered Dacrydium pierrei
Publikováno v:
Open Life Sciences, Vol 12, Iss 1, Pp 345-355 (2017)
Because growth environment is affected by climate change, Dacrydium pierrei resources are becoming less and less. Therefore, understanding the effects of environmental variables on seedling-sapling distributions can help gain insight into changes in
Externí odkaz:
https://doaj.org/article/78c6508016b84306b49587b0f3650e57
Discrete-choice models, such as Multinomial Logit, Probit, or Mixed-Logit, are widely used in Marketing, Economics, and Operations Research: given a set of alternatives, the customer is modeled as choosing one of the alternatives to maximize a (laten
Externí odkaz:
http://arxiv.org/abs/2310.08716
Electrifying heavy-duty trucks offers a substantial opportunity to curtail carbon emissions, advancing toward a carbon-neutral future. However, the inherent challenges of limited battery energy and the sheer weight of heavy-duty trucks lead to reduce
Externí odkaz:
http://arxiv.org/abs/2310.04440
As artificial intelligence (AI) systems play an increasingly prominent role in human decision-making, challenges surface in the realm of human-AI interactions. One challenge arises from the suboptimal AI policies due to the inadequate consideration o
Externí odkaz:
http://arxiv.org/abs/2310.00817
Discrete-choice models are used in economics, marketing and revenue management to predict customer purchase probabilities, say as a function of prices and other features of the offered assortment. While they have been shown to be expressive, capturin
Externí odkaz:
http://arxiv.org/abs/2308.05617