23 citations · 40 across the 14 of their papers we have counts for
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cs.CV2025
Performance is not All You Need: Sustainability Considerations for Algorithms
Xiang Li, Chong Zhang, Hongpeng Wang +3
This work focuses on the high carbon emissions generated by deep learning model training, specifically addressing the core challenge of balancing algorithm performance and energy c…
cs.CL2025
Semantic-Preserving Prompt Hijacking: A Black-Box Adversarial Attack on Auto-Prompt Optimization
Chong Zhang, Xiang Li, Jia Wang +3
LLMs increasingly integrate auto-suggestion optimization modules, enabling them to rewrite and display user input before generating the final response. While this design aims to en…
cs.CL2025★ 1 cited
Efficient and Stealthy Jailbreak Attacks via Adversarial Prompt Distillation from LLMs to SLMs
Xiang Li, Chong Zhang, Jia Wang +3
Current jailbreak attacks on large language models (LLMs) predominantly rely on LLMs themselves to generate adversarial prompts, creating a critical efficiency bottleneck: each att…