papers

Publications (10)

cs.CR2025

Modification and Generated-Text Detection: Achieving Dual Detection Capabilities for the Outputs of LLM by Watermark

Yuhang Cai, Yaofei Wang, Donghui Hu +1

The development of large language models (LLMs) has raised concerns about potential misuse. One practical solution is to embed a watermark in the text, allowing ownership verificat…

cond-mat.supr-con2016

Critical Current Survival in YBCO Superconducting Layer of the Delaminated Coated Conductor

Feng Feng, Qishu Fu, Timing Qu +8

High temperature superconducting coated conductor (CC) could be practically applied in electric equipment due to its favorable mechanical properties and the critical current perfor…

physics.geo-ph2023

Bayesian Neural Networks for Geothermal Resource Assessment: Prediction with Uncertainty

Stephen Brown, William L. Rodi, Marco Seracini +5

We consider the application of machine learning to the evaluation of geothermal resource potential. A supervised learning problem is defined where maps of 10 geological and geophys…

eess.SP2021

The Effect of Ground Truth Accuracy on the Evaluation of Localization Systems

Chen Gu, Ahmed Shokry, Moustafa Youssef

The ability to accurately evaluate the performance of location determination systems is crucial for many applications. Typically, the performance of such systems is obtained by com…

stat.AP2020

Bayesian waveform-based calibration of high-pressure acoustic emission systems with ball drop measurements

Chen Gu, Ulrich Mok, Youssef M. Marzouk +4

Acoustic emission (AE) is a widely used technology to study source mechanisms and material properties during high-pressure rock failure experiments. It is important to understand t…

stat.CO2024

Greedy selection of optimal location of sensors for uncertainty reduction in seismic moment tensor inversion

Ben Mansour Dia, Michael Fehler, SanLinn I. Kaka +3

We address an optimal sensor placement problem through Bayesian experimental design for seismic full waveform inversion for the recovery of the associated moment tensor. The object…

cs.CR2026

PromptGraph: Graph-Guided Prompt Sanitization for Balancing Privacy and Utility in LLM Inference

Chen Gu, Hui Wan, Donghui Hu +2

Large Language Model (LLM) services introduce a fundamental privacy challenge. Sensitive information may be inferred not only from explicit identifiers, such as names or phone numb…

cs.CR2025

Approximate Gaussian Mapping for Generative Image Steganography

Yuhua Xu, Wei Sun, Chengpei Tang +3

Ordinary differential equation (ODE)-based diffusion models enable deterministic image synthesis, establishing a reversible mapping suitable for generative steganography. While pre…

cond-mat.mes-hall2025

High harmonic generation light source with polarization selectivity and sub-100-m beam size for time- and angle-resolved photoemission spectroscopy

Haoyuan Zhong, Xuanxi Cai, Changhua Bao +9

High-quality ultrafast light sources are critical for developing advanced time- and angle-resolved photoemission spectroscopy (TrARPES). While the application of high harmonic gene…

cs.LG2025

FLClear: Visually Verifiable Multi-Client Watermarking for Federated Learning

Chen Gu, Yingying Sun, Yifan She +1

Federated learning (FL) enables multiple clients to collaboratively train a shared global model while preserving the privacy of their local data. Within this paradigm, the intellec…