UniEvo-VL: Self-Distillation Training for Multimodal Model Self-Improvement
Motivated by this unified capacity, we introduce UniEvo-VL, a self-evolving framework for multimodal models to learn from this constructive self-correction feedback during test-time compute. Instead of relying on a separate, often larger, teacher, we leverage their self-critiques as privileged information and ask a single multimodal model to act as both teacher and student with different contexts. The student only sees the vanilla question, while the teacher conditions on the privileged critique.
- ▪Motivated by this unified capacity, we introduce UniEvo-VL, a self-evolving framework for multimodal models to learn from this constructive self-correction feedback during test-time compute.
- ▪Instead of relying on a separate, often larger, teacher, we leverage their self-critiques as privileged information and ask a single multimodal model to act as both teacher and student with different contexts.
- ▪The student only sees the vanilla question, while the teacher conditions on the privileged critique.
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| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2609.38721 |
| Publication time | Tue, 06 Oct 2026 22:51:35 +0000 |
| Retrieval time | 2026-10-07T00:33:01.767Z |
| Last seen | 2026-10-07T00:33:01.767Z |
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Computer Science > Artificial Intelligence arXiv:2609.38721 (cs) [Submitted on 30 Sep 2026] Title:UniEvo-VL: An On-policy Self-Distillation Training Recipe for Multimodal Model Self-improvement Authors:Fang Wu, Da Xing, Yanjie Huang, Junxi Wang, Ji Wang, Hejia Geng, Guancheng Wan, Bowen Zuo, Xiaomin Li, Shixiang Tang, Xinyu Xiang, Zehong Wang, Shiyi Du, Peng Xia, Shuangjia Zheng, Yining Hong, Li Erran Li, Jure Leskovec, Yejin Choi View a PDF of the paper titled UniEvo-VL: An On-policy Self-Distillation Training Recipe for Multimodal Model Self-improvement, by Fang Wu and 18 other authors View PDF HTML (experimental) Abstract:Modern multimodal models bring generation and understanding into a single unified system, which enables them to provide and learn from their own feedback.
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