4 papers
IAPT: Instruction-Aware Prompt Tuning for Large Language Models
Wei Zhu, Aaron Xuxiang Tian, Congrui Yin +3
Soft prompt tuning is a widely studied parameter-efficient fine-tuning method. However, it has a clear drawback: many soft tokens must be inserted into the input sequences to guara…
Text2MDT: Extracting Medical Decision Trees from Medical Texts
Wei Zhu, Wenfeng Li, Xing Tian +6
Knowledge of the medical decision process, which can be modeled as medical decision trees (MDTs), is critical to build clinical decision support systems. However, the current MDT c…
Unified Demonstration Retriever for In-Context Learning
Xiaonan Li, Kai Lv, Hang Yan +6
In-context learning is a new learning paradigm where a language model conditions on a few input-output pairs (demonstrations) and a test input, and directly outputs the prediction.…
Filter Pruning via Filters Similarity in Consecutive Layers
Xiaorui Wang, Jun Wang, Xin Tang +3
Filter pruning is widely adopted to compress and accelerate the Convolutional Neural Networks (CNNs), but most previous works ignore the relationship between filters and channels i…