Lens VLM is a 9B Vision Language Model (VLM) that scans compressed images of text, then selectively expands only the relevant pages to their uncompressed form via learned tools.\n\nPaper: Lens VLM: Selective Context Expansion for Compressed Visual Representation of Text. Code: https://github.com/apple-aiml-research/ml-lensvlm. License: All ML model files in this repository, including Apple's modifications to the Qwen model, are provided under the terms of the Apple Machine Learning Research Model License.

The source code that accompanies this model is distributed separately and is provided under the terms of the Apple Sample Code License.\n\nUsage: Install the Lens VLM code and run inference. For a custom document, use the demo with compression options: 5x, 10x, 15x. See the repository README for data preparation and evaluation.\n\nCitation: @article{xie2026lensvlm, title={Lens VLM: Selective Context Expansion for Compressed Visual Representation of Text}, author={Xie, Roy and Friedman, Dan and Yu, Donghan and Pan, Bowen and Fifty, Christopher and Kim, Jang-Hyun and Du, Xianzhi and Gan, Zhe and Rathod, Vivek and Dhingra, Bhuwan}, journal={arXiv preprint arXiv:2605.07019}, year={2026}}.