491 citations · 632 across the 24 of their papers we have counts for
4 papers · 1 filter
ELFS: Label-Free Coreset Selection with Proxy Training Dynamics
Haizhong Zheng, Elisa Tsai, Yifu Lu +4
High-quality human-annotated data is crucial for modern deep learning pipelines, yet the human annotation process is both costly and time-consuming. Given a constrained human label…
PRP: Propagating Universal Perturbations to Attack Large Language Model Guard-Rails
Neal Mangaokar, Ashish Hooda, Jihye Choi +4
Large language models (LLMs) are typically aligned to be harmless to humans. Unfortunately, recent work has shown that such models are susceptible to automated jailbreak attacks th…
Plato: Plan to Efficiently Decode for Large Language Model Inference
Shuowei Jin, Xueshen Liu, Yongji Wu +7
Large language models (LLMs) have achieved remarkable success in natural language tasks, but their inference incurs substantial computational and memory overhead. To improve effici…
Learn To be Efficient: Build Structured Sparsity in Large Language Models
Haizhong Zheng, Xiaoyan Bai, Xueshen Liu +4
Large Language Models (LLMs) have achieved remarkable success with their billion-level parameters, yet they incur high inference overheads. The emergence of activation sparsity in…