3 papers
cs.CL2026
FNF: Functional Network Fingerprint for Large Language Models
Yiheng Liu, Junhao Ning, Sichen Xia +8
The development of large language models (LLMs) is costly and has significant commercial value. Consequently, preventing unauthorized appropriation of open-source LLMs and protecti…
cs.CL2025
Pruning Large Language Models by Identifying and Preserving Functional Networks
Yiheng Liu, Junhao Ning, Sichen Xia +5
Structured pruning is one of the representative techniques for compressing large language models (LLMs) to reduce GPU memory consumption and accelerate inference speed. It offers s…
cs.CL2024
Analyzing Nobel Prize Literature with Large Language Models
Zhenyuan Yang, Zhengliang Liu, Jing Zhang +19
This study examines the capabilities of advanced Large Language Models (LLMs), particularly the o1 model, in the context of literary analysis. The outputs of these models are compa…