activity
20232026
most citedPrompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts

8 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Plan2Cleanse: Test-Time Backdoor Defense via Monte-Carlo Planning in Deep Reinforcement Learning

Sze-Ann Chen, Zhi-Yi Chin, Kui-Yuan Chen +2

Ensuring the security of reinforcement learning (RL) models is critical, particularly when they are trained by third parties and deployed in real-world systems. Attackers can impla…

cs.LG2024★ 1 cited

Red-Teaming Text-to-Image Models via In-Context Experience Replay and Semantic-Preserving Prompt Rewriting

Zhi-Yi Chin, Pin-Yu Chen, Wei-Chen Chiu +1

Understanding the capabilities of text-to-image (T2I) models in harmful content generation is essential to safety and compliance. However, human red-teaming is costly and inconsist…

cs.CV2024★ 1 cited

Realizing Video Summarization from the Path of Language-based Semantic Understanding

Kuan-Chen Mu, Zhi-Yi Chin, Wei-Chen Chiu

The recent development of Video-based Large Language Models (VideoLLMs), has significantly advanced video summarization by aligning video features and, in some cases, audio feature…

cs.CV2023

Masking Improves Contrastive Self-Supervised Learning for ConvNets, and Saliency Tells You Where

Zhi-Yi Chin, Chieh-Ming Jiang, Ching-Chun Huang +2

While image data starts to enjoy the simple-but-effective self-supervised learning scheme built upon masking and self-reconstruction objective thanks to the introduction of tokeniz…

cs.CL2023★ 8 cited

Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts

Zhi-Yi Chin, Chieh-Ming Jiang, Ching-Chun Huang +2

Text-to-image diffusion models, e.g. Stable Diffusion (SD), lately have shown remarkable ability in high-quality content generation, and become one of the representatives for the r…