1 citations · 2 across the 5 of their papers we have counts for
5 papers
Moving sample method for solving time-dependent partial differential equations
Beining Xu, Haijun Yu, Jiayu Zhai +2
Solving time-dependent partial differential equations (PDEs) that exhibit sharp gradients or local singularities is computationally demanding, as traditional physics-informed neura…
TECP: Token-Entropy Conformal Prediction for LLMs
Beining Xu, Yongming Lu
Uncertainty quantification (UQ) for open-ended language generation remains a critical yet underexplored challenge, especially under black-box constraints where internal model signa…
Understanding the Effects of RLHF on the Quality and Detectability of LLM-Generated Texts
Beining Xu, Arkaitz Zubiaga
Large Language Models (LLMs) have demonstrated exceptional performance on a range of downstream NLP tasks by generating text that closely resembles human writing. However, the ease…
Adaptable and Precise: Enterprise-Scenario LLM Function-Calling Capability Training Pipeline
Guancheng Zeng, Wentao Ding, Beining Xu +8
Enterprises possess a vast array of API assets scattered across various functions, forming the backbone of existing business processes. By leveraging these APIs as functional tools…
A Quantitative Approach to Understand Self-Supervised Models as Cross-lingual Feature Extractors
Shuyue Stella Li, Beining Xu, Xiangyu Zhang +3
In this work, we study the features extracted by English self-supervised learning (SSL) models in cross-lingual contexts and propose a new metric to predict the quality of feature…