most citedThe Science of Detecting LLM-Generated Texts

50 citations · 67 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL20241 cited

Learning to Compress Prompt in Natural Language Formats

Yu-Neng Chuang, Tianwei Xing, Chia-Yuan Chang +3

Large language models (LLMs) are great at processing multiple natural language processing tasks, but their abilities are constrained by inferior performance with long context, slow…

cs.AI2024

Feasibility of Identifying Factors Related to Alzheimer's Disease and Related Dementia in Real-World Data

Aokun Chen, Qian Li, Yu Huang +7

A comprehensive view of factors associated with AD/ADRD will significantly aid in studies to develop new treatments for AD/ADRD and identify high-risk populations and patients for…

cs.IR20231 cited

DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research

Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang +8

The exponential growth in scholarly publications necessitates advanced tools for efficient article retrieval, especially in interdisciplinary fields where diverse terminologies are…

cs.LG20231 cited

CODA: Temporal Domain Generalization via Concept Drift Simulator

Chia-Yuan Chang, Yu-Neng Chuang, Zhimeng Jiang +3

In real-world applications, machine learning models often become obsolete due to shifts in the joint distribution arising from underlying temporal trends, a phenomenon known as the…

cs.CV2023

DISPEL: Domain Generalization via Domain-Specific Liberating

Chia-Yuan Chang, Yu-Neng Chuang, Guanchu Wang +2

Domain generalization aims to learn a generalization model that can perform well on unseen test domains by only training on limited source domains. However, existing domain general…

cs.LG20233 cited

CoRTX: Contrastive Framework for Real-time Explanation

Yu-Neng Chuang, Guanchu Wang, Fan Yang +4

Recent advancements in explainable machine learning provide effective and faithful solutions for interpreting model behaviors. However, many explanation methods encounter efficienc…