activity
20222024
most citedIntegration of cognitive tasks into artificial general intelligence test for large models

1 citations · 3 across the 7 of their papers we have counts for

collaborators

7 papers

q-bio.NC2024

CoCoG-2: Controllable generation of visual stimuli for understanding human concept representation

Chen Wei, Jiachen Zou, Dietmar Heinke +1

Humans interpret complex visual stimuli using abstract concepts that facilitate decision-making tasks such as food selection and risk avoidance. Similarity judgment tasks are effec…

q-bio.NC2024

Reverse engineering the brain input: Network control theory to identify cognitive task-related control nodes

Zhichao Liang, Yinuo Zhang, Jushen Wu +1

The human brain receives complex inputs when performing cognitive tasks, which range from external inputs via the senses to internal inputs from other brain regions. However, the e…

cs.AI20241 cited

Integration of cognitive tasks into artificial general intelligence test for large models

Youzhi Qu, Chen Wei, Penghui Du +10

During the evolution of large models, performance evaluation is necessarily performed to assess their capabilities and ensure safety before practical application. However, current…

eess.SP20241 cited

Advancing EEG/MEG Source Imaging with Geometric-Informed Basis Functions

Song Wang, Chen Wei, Kexin Lou +2

Electroencephalography (EEG) and Magnetoencephalography (MEG) are pivotal in understanding brain activity but are limited by their poor spatial resolution. EEG/MEG source imaging (…

eess.SP2023

Perturbing a Neural Network to Infer Effective Connectivity: Evidence from Synthetic EEG Data

Peizhen Yang, Xinke Shen, Zongsheng Li +3

Identifying causal relationships among distinct brain areas, known as effective connectivity, holds key insights into the brain's information processing and cognitive functions. El…

cs.LG2022

Partial Least Square Regression via Three-factor SVD-type Manifold Optimization for EEG Decoding

Wanguang Yin, Zhichao Liang, Jianguo Zhang +1

Partial least square regression (PLSR) is a widely-used statistical model to reveal the linear relationships of latent factors that comes from the independent variables and depende…