Xuandong Zhao

Orcid: 0009-0008-7888-2783

According to our database1, Xuandong Zhao authored at least 28 papers between 2019 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
An undetectable watermark for generative image models.
IACR Cryptol. ePrint Arch., 2024

Multimodal Situational Safety.
CoRR, 2024

Efficiently Identifying Watermarked Segments in Mixed-Source Texts.
CoRR, 2024

Evaluating Durability: Benchmark Insights into Multimodal Watermarking.
CoRR, 2024

Bileve: Securing Text Provenance in Large Language Models Against Spoofing with Bi-level Signature.
CoRR, 2024

MarkLLM: An Open-Source Toolkit for LLM Watermarking.
CoRR, 2024

Mapping the Increasing Use of LLMs in Scientific Papers.
CoRR, 2024

Perils of Self-Feedback: Self-Bias Amplifies in Large Language Models.
CoRR, 2024

Permute-and-Flip: An optimally robust and watermarkable decoder for LLMs.
CoRR, 2024

Weak-to-Strong Jailbreaking on Large Language Models.
CoRR, 2024

Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

DE-COP: Detecting Copyrighted Content in Language Models Training Data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Provable Robust Watermarking for AI-Generated Text.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

A Survey on Detection of LLMs-Generated Content.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Chatbot and Fatigued Driver: Exploring the Use of LLM-Based Voice Assistants for Driving Fatigue.
Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2024

Pride and Prejudice: LLM Amplifies Self-Bias in Self-Refinement.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
Generative Autoencoders as Watermark Attackers: Analyses of Vulnerabilities and Threats.
CoRR, 2023

Private Prediction Strikes Back! Private Kernelized Nearest Neighbors with Individual Rényi Filter.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Protecting Language Generation Models via Invisible Watermarking.
Proceedings of the International Conference on Machine Learning, 2023

Pre-trained Language Models Can be Fully Zero-Shot Learners.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Provably Confidential Language Modelling.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Distillation-Resistant Watermarking for Model Protection in NLP.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Compressing Sentence Representation for Semantic Retrieval via Homomorphic Projective Distillation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021
An Optimal Reduction of TV-Denoising to Adaptive Online Learning.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
A Multi-Semantic Metapath Model for Large Scale Heterogeneous Network Representation Learning.
CoRR, 2020

2019
Multi-Size Computer-Aided Diagnosis Of Positron Emission Tomography Images Using Graph Convolutional Networks.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Predicting Alzheimer's Disease by Hierarchical Graph Convolution from Positron Emission Tomography Imaging.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019


  Loading...