12 papers
FSDBN: Foreground-Aware EEG-Visual Alignment via Dynamic Brain Networks
Yiheng Liu, Chuhang Zheng, Peiliang Gong +3
EEG-based visual decoding provides a non-invasive pathway for interpreting visual semantics. However, existing methods often overlook the perceptual asymmetry between foreground an…
Multi-Level Bidirectional Biomimetic Learning for EEG-Based Visual Decoding
Jingtao Liu, Peiliang Gong, Chuhang Zheng +2
EEG-based visual neural decoding aims to align neural responses with visual stimuli for tasks such as image retrieval. However, limited paired data and a fundamental mismatch betwe…
Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research
Tianyang Zhong, Zhenyuan Yang, Zhengliang Liu +11
Low-resource languages serve as invaluable repositories of human history, embodying cultural evolution and intellectual diversity. Despite their significance, these languages face…
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…
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…
VAR RL Done Right: Tackling Asynchronous Policy Conflicts in Visual Autoregressive Generation
Shikun Sun, Liao Qu, Huichao Zhang +8
Visual generation is dominated by three paradigms: AutoRegressive (AR), diffusion, and Visual AutoRegressive (VAR) models. Unlike AR and diffusion, VARs operate on heterogeneous in…