IEEE

Subspace Representation Learning for Sparse Linear Arrays to Localize More Sources Than Sensors: A Deep Learning Methodology

Abstract: Localizing more sources than sensors with a sparse linear array (SLA) has long relied on minimizing a distance between two covariance matrices and recent algorithms often utilize ...

Language shapes visual processing in both human brains and AI models, study finds

Neuroscientists have been trying to understand how the brain processes visual information for over a century. The development of computational models inspired by the brain's layered organization, also ...
GitHub

Efficient Visual Representation Learning with Bidirectional State Space Model

May. 2nd, 2024: Vision Mamba (Vim) is accepted by ICML2024. 🎉 Conference page can be found here. Feb. 10th, 2024: We update Vim-tiny/small weights and training scripts. By placing the class token at ...
GitHub

Don’t Blind Your VLA: Aligning Visual Representations for OOD Generalization

To address the degradation of visual-language (VL) representations during VLA supervised fine-tuning (SFT), we introduce Visual Representation Alignment. During SFT, we pull a VLA’s visual tokens ...
Microsoft

LLM2CLIP: Powerful Language Model Unlocks Richer Visual Representation

CLIP is one of the most important multimodal foundational models today. What powers CLIP’s capabilities? The rich supervision signals provided by natural language, the carrier of human knowledge, ...
IEEE

Reconstructing Visual Stimulus Representation From EEG Signals Based on Deep Visual Representation Model

Abstract: Reconstructing visual stimulus representation is a significant task in neural decoding. Until now, most studies have considered functional magnetic resonance imaging (fMRI) as the signal ...