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**TL;DR**: Trash to Treasure introduces **DualityForge**, a controllable diffusion-based framework that turns real videos into counterfactual ones, automatically generating paired videos and QA data for contrastive training. Based on the large-scale **DualityVidQA** dataset and the proposed **DNA-Train** SFT–RL regime with ℓ1-normalized advantages, our approach reduces hallucinations in multimodal LLMs by 24% and shows strong generalization across benchmarks. Dataset and code will be released.
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## Method Overview
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<img width="1678" height="980" alt="image" src="https://github.com/user-attachments/assets/a72a0ee9-7927-4ad0-9ad4-1ba448cbb0e8" />
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## Update
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## 📎 Citation
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