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README.md
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---
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license: mit
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---
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# IVT-LR (Chameleon)
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## Overview
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This model was presented in the paper [Reasoning in the Dark: Interleaved Vision-Text Reasoning in Latent Space](https://huggingface.co/papers/2510.12603).
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Interleaved Vision-Text Latent Reasoning (IVT-LR) is the first VLM framework that unifies textual and visual representations in the latent space and implements multimodal latent reasoning. Specifically, IVT-LR represents each reasoning step by combining two implicit parts: **latent text** and **latent vision**. We further introduce a progressive multi-stage training strategy to enable MLLMs to perform the above multimodal latent reasoning steps.
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---
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## Usage
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This repository provides pretrained Chameleon models for IVT-LR on **M3CoT** and **ScienceQA** datasets.
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To see detailed usage, including inference code and scripts for training, please refer to the [GitHub repository](https://github.com/ModalityDance/IVT-LR).
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---
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### Download Models
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You can download the models directly from Hugging Face using `huggingface_hub`:
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```python
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from huggingface_hub import hf_hub_download
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# Download Chameleon model trained on M3CoT
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chameleon_m3cot_path = hf_hub_download("ModalityDance/IVTLR_CHAMELEON_M3COT", "model.pth")
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# Download Chameleon model trained on ScienceQA
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chameleon_sqa_path = hf_hub_download("ModalityDance/IVTLR_CHAMELEON_SQA", "model.pth")
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```
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