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

Shared serializers and models for Visual Studio solution files. Handles traditional .sln file and new .slnx file.

Serializers for solution files, traditional text based .sln file, and XML based .slnx file. Object model for manipulating file contents in common way. SLN File Format Consistent with legacy Visual ...
IEEE

NVILA: Efficient Frontier Visual Language Models

Abstract: Visual language models (VLMs) have made significant advances in accuracy in recent years. However, their efficiency has received much less attention. This paper introduces NVILA, a family of ...
IEEE

Mitigating Object Hallucination in Large Vision-Language Models via Visual Attention Direct Preference Optimization

Abstract: Large Vision-Language Models (LVLMs) suffer from severe object hallucinations, leading them to frequently generate outputs that do not correspond to the image content, significantly reducing ...
InfoWorld

Microsoft MCP server gives AI assistants access to MSBuild logs

The Microsoft Binlog MCP Server enables AI-powered build failure diagnosis, property tracing, performance analysis, and build ...