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VLM-R1 - AI Vision Models Tool

Overview

VLM-R1 is an open-source, R1-style large vision–language model designed for robust visual understanding across tasks such as Referring Expression Comprehension (REC) and rigorous out-of-domain evaluation. According to the GitHub repository, the project emphasizes stability and generalization in the model family and provides end-to-end training scripts, evaluation utilities, and example configurations to reproduce reported results. The authors highlight support for Reinforcement Learning (RL)-based fine-tuning workflows that further improve task-specific performance. The codebase targets research and production experimentation: it includes multi-node training support and multi-image input handling to enable scalable training and complex visual input scenarios. The repository documents training and evaluation pipelines, making it suitable for researchers wanting to benchmark REC, out-of-domain robustness, and RL fine-tuning methods. For complete implementation details, reproducibility instructions, and up-to-date results, refer to the project on GitHub.

Installation

Install via pip:

git clone https://github.com/om-ai-lab/VLM-R1.git
cd VLM-R1
pip install -r requirements.txt

Key Features

  • R1-style large vision-language architecture focused on stable, generalizable visual understanding
  • Referring Expression Comprehension (REC) benchmarks and evaluation scripts included
  • Out-of-domain evaluation utilities for assessing cross-dataset robustness
  • Multi-node training support for distributed model optimization
  • Multi-image input handling for complex visual contexts and composite scenes
  • Reinforcement Learning (RL)-based fine-tuning workflows to improve downstream performance
  • Reproducible training scripts and configuration files for experiment replication

Community

The project is hosted on GitHub under the om-ai-lab organization; the repository contains code, training scripts, and evaluation tools. According to the repository, contributions and issues are handled through standard GitHub workflows (issues, pull requests). For the latest activity, release notes, or implementation questions, consult the project's GitHub page and the repository's issue tracker.

Last Refreshed: 2026-01-09

Key Information

  • Category: Vision Models
  • Type: AI Vision Models Tool
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