5 papers
Mapping Text to Multiplex Graph: Prompt Compression as Lévy Walk-Guided Graph Pruning
Yaxin Gao, Yao Lu, Jinhong Deng +7
Existing prompt compression methods treat text as flat token sequences, failing to capture the distributed nature of important information, which is often spread across multiple lo…
DSPC: Dual-Stage Progressive Compression Framework for Efficient Long-Context Reasoning
Yaxin Gao, Yao Lu, Zongfei Zhang +3
Large language models (LLMs) have achieved remarkable success in many natural language processing (NLP) tasks. To achieve more accurate output, the prompts used to drive LLMs have…
LoRALib: A Standardized Benchmark for Evaluating LoRA-MoE Methods
Shaoheng Wang, Yao Lu, Yuqi Li +5
As a parameter efficient fine-tuning (PEFT) method, low-rank adaptation (LoRA) can save significant costs in storage and computing, but its strong adaptability to a single task is…
ReStNet: A Reusable & Stitchable Network for Dynamic Adaptation on IoT Devices
Maoyu Wang, Yao Lu, Jiaqi Nie +4
With the rapid development of deep learning, a growing number of pre-trained models have been publicly available. However, deploying these fixed models in real-world IoT applicatio…
An effective method for profiling core-periphery structures in complex networks
Jiaqi Nie, Qi Xuan, Dehong Gao +1
Profiling core-periphery structures in networks has attracted significant attention, leading to the development of various methods. Among these, the rich-core method is distinguish…