Author

Lin Xu

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#machine learning Preprint Sep 2026

PE-OPSD: Internalizing Prompt Enhancement into Flow-matching Models via On-Policy Self-Distillation

Text-to-image users often provide concise and underspecified prompts, whereas generative models benefit from detailed textual conditions for reliable instruction following. Existing systems bridge this gap with Prompt Enhancers (PEs) that rewrite raw prompts at inference time, introducing additional latency and leaving...

Ming-Hung Lin, Cheng-Fei Cai, Lin Xu et al. · 0 citations

Jul 2026

MixDiffusion: Mixing Diffusion-based Uni-condition Text-to-Image Generation Models for Multi-condition Image Synthesis

Recent advances in text-to-image (T2I) generation have enabled controllable image synthesis by incorporating conditions beyond text. However, most existing diffusion-based methods are limited to a single type of control condition (e.g., bounding boxes or keypoints), which restricts their flexibility. To address this li...

Pengcheng Wan, Liang Han, Lin Xu et al. · arXiv.org · 0 citations

Preprint Aug 2026

DreOPD: Degraded-Reference Extrapolative On-Policy Distillation for Flow-matching Models

This work proposes DreOPD, a Degraded-reference extrapolative OPD method for flow-matching models that bridges these two paradigms, and converts implicit reward extrapolation into closed-form velocity regression, enabling extrapolative post-training with the stability of OPD.

Ming-Hung Lin, Cheng-Fei Cai, Lin Xu et al. · 2 citations