Work

Sparse Brains are Also Adaptive Brains: Cognitive-Load-Aware Dynamic Activation for LLMs

Year: 2026

Type: conference-paper

Abstract: Dense large language models (LLMs) face critical efficiency bottlenecks, as they rigidly activate all parameters regardless of input complexity.While existing sparsity methods (static pruning or dynamic activation) partially address this issue, they either lack adaptivity to contextual or model structural demands or incur prohibitive computational overhead.Inspired by the human brain's dual-process mechanisms -predictive coding (N400) for backbone sparsity and structural reanalysis (P600) for complex contexts -we propose CLADA, a Cognitive-Load-Aware Dynamic Activation framework that synergizes statistical sparsity with semantic adaptability.

Source: Findings of the Association for Computational Linguistics: EACL

DOI: 10.18653/v1/2026.findings-eacl.270

Authors: Yiheng Yang, Yujie Wang, Chi Ma, Lei Yu, Emmanuele Chersoni, Chu-Ren Huang

Institutions: Hong Kong Polytechnic University, Zhejiang University, Meituan (China)

Language: English

Topic: Advanced Neural Network Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W7140130395

FWCI: 8.904

Cites:

Cited by: 1

Related to: 10