In the recent past, more than 5 years or so, DL especially the large language models (LLMs)
has generated extensive studies out of a distinctly average downturn field of knowledge …

In the era of Artificial Intelligence Generated Content (AIGC), conditional multimodal
synthesis technologies (eg, text-to-image) are dynamically reshaping the natural content …

Reconstructing visual stimuli from brain recordings has been a meaningful and challenging
task. Especially, the achievement of precise and controllable image reconstruction bears …

Due to the lack of paired samples and the low signal-to-noise ratio of functional MRI (fMRI)
signals, reconstructing perceived natural images or decoding their semantic contents from …

How to decode human vision through neural signals has attracted a long-standing interest in
neuroscience and machine learning. Modern contrastive learning and generative models …

Electroencephalogram (EEG) is a brain signal known for its high time resolution and
moderate signal-to-noise ratio. Whether natural images can be decoded from EEG has been …

As a multimodal form of hate speech on social media, hateful memes are more aggressive
and cryptic threats to the real life of humans. Automatic detection of hateful memes is crucial …

Advances in artificial intelligence enable neural networks to learn a wide variety of tasks, yet
our understanding of the learning dynamics of these networks remains limited. Here, we …

The exploration of brain activity and its decoding from fMRI data has been a longstanding
pursuit, driven by its potential applications in brain-computer interfaces, medical diagnostics …

Abstract We introduce Mind Artist (MindArt) a novel and efficient neural decoding
architecture to snap artistic photographs from our mind in a controllable manner. Recently …