GitHub

SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference

In vision-language models (VLMs), visual tokens usually consume a significant amount of computational overhead, despite their sparser information density compared to text tokens. To address this, ...
IEEE

CLIP-Vision Guided Few-Shot Metal Surface Defect Recognition

Abstract: Metal surface defect recognition (MSDR) based on deep learning encounters the challenge of few-shot expert-labeled data. In this study, we proposed a CLIP-vision guided self supervised ...
Interesting Engineering

US: Los Alamos lab’s new tool detects hallucinations in machine vision models

Researchers at Los Alamos National Laboratory have developed a new tool called the Prelim Attention Score, or PAS, to help detect when a vision-language model’s output is grounded in the image and ...
IEEE

Efficient Sedimentary Facies Recognition Using Vision Transformer and Weakly Supervised Deep Multi-View Clustering

Abstract: Sedimentary facies recognition plays a crucial role in geological exploration and oil-gas resource evaluation. However, traditional recognition methods are limited by their ability to ...