activity
20242026
collaborators

5 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…

q-bio.NC2026

Brain-Inspired Exploration of Functional Networks and Key Neurons in Large Language Models

Yiheng Liu, Zhengliang Liu, Zihao Wu +10

In recent years, the rapid advancement of large language models (LLMs) in natural language processing has sparked significant interest among researchers to understand their mechani…

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.CY2025

Bridging Technology and Humanities: Evaluating the Impact of Large Language Models on Social Sciences Research with DeepSeek-R1

Peiran Gu, Fuhao Duan, Wenhao Li +6

In recent years, the development of Large Language Models (LLMs) has made significant breakthroughs in the field of natural language processing and has gradually been applied to th…

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…