2 citations · 2 across the 7 of their papers we have counts for
7 papers
TAAC: A gate into Trustable Audio Affective Computing
Xintao Hu, Feng-Qi Cui
With the emergence of AI techniques for depression diagnosis, the conflict between high demand and limited supply for depression screening has been significantly alleviated. Among…
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…
Jacobian-Based Interpretation of Nonlinear Neural Encoding Model
Xiaohui Gao, Haoran Yang, Yue Cheng +4
In recent years, the alignment between artificial neural network (ANN) embeddings and blood oxygenation level dependent (BOLD) responses in functional magnetic resonance imaging (f…
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…
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…
Brain-like Functional Organization within Large Language Models
Haiyang Sun, Lin Zhao, Zihao Wu +7
The human brain has long inspired the pursuit of artificial intelligence (AI). Recently, neuroimaging studies provide compelling evidence of alignment between the computational rep…
LinBridge: A Learnable Framework for Interpreting Nonlinear Neural Encoding Models
Xiaohui Gao, Yue Cheng, Peiyang Li +7
Neural encoding of artificial neural networks (ANNs) links their computational representations to brain responses, offering insights into how the brain processes information. Curre…