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, ...
GitHub

PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction (CVPR 2025)

[2025.3.6] [Update🔥] Please place any models that need to be compatible with pdrop in this issue [2025.2.27] 🚀 Our paper has been accepted by CVPR 2025!!! [2024.10.24] 🚀 Our paper has been featured ...
IEEE

ChipVQA: Benchmarking Visual Language Models for Chip Design

Abstract: Large-language models (LLMs) have exhibited great potential to assist chip designs and analysis. Recent research and efforts are mainly focusing on text-based tasks including general QA, ...
IEEE

Progressive Semantic-Visual Alignment and Refinement for Vision-Language Tracking

In recent years, vision-language tracking has drawn emerging attention in the tracking field. The critical challenge for the task is to fuse semantic representations of language information and visual ...