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Biru Zhu

4 accepted papers

2026

Towards Human-Imperceptible Backdoor Attacks on Text-to-Image Diffusion Models

CVPR 2026

Deep learning models are well known to be susceptible to backdoor attacks, and text-to-image generation models are no exception. When a specific trigger is embedded in the input, a backdoored model can be manipulated to perform attacker-defined malicious behaviors, such as generating harmful or inap

Cited by 0SourceScholar
2023

Beat LLMs at Their Own Game: Zero-Shot LLM-Generated Text Detection via Querying ChatGPT

EMNLP 2023short main

Large language models (LLMs), e.g., ChatGPT, have revolutionized the domain of natural language processing because of their excellent performance on various tasks. Despite their great potential, LLMs also incur serious concerns as they are likely to be misused. There are already reported cases of ac…

Cited by 0SourcecodeScholar
2022

Moderate-fitting as a Natural Backdoor Defender for Pre-trained Language Models

NeurIPS 2022accept

Despite the great success of pre-trained language models (PLMs) in a large set of natural language processing (NLP) tasks, there has been a growing concern about their security in real-world applications. Backdoor attack, which poisons a small number of training samples by inserting backdoor trigger…

2022

Pass off Fish Eyes for Pearls: Attacking Model Selection of Pre-trained Models

ACL 2022long

Selecting an appropriate pre-trained model (PTM) for a specific downstream task typically requires significant efforts of fine-tuning. To accelerate this process, researchers propose feature-based model selection (FMS) methods, which assess PTMs’ transferability to a specific task in a fast way with…