Haozhi Yuan, Handong Li, Yifan Zhang, Qianshan Wei (Nanjing University) · Visual Agent Distillation
Reframe: Observation-Aligned Multi-Teacher On-Policy Distillation for Agentic Visual Reasoning
Reframe is a post-training framework for visual agents that aligns the observation state returned by tools, not only the output distribution. It combines Ground-Drop-GRPO, which trains spatial and temporal specialists with evidence-aware rewards and stochastic removal of the input image, and Observation-Gated-MOPD, which replaces deficient tool actions mid-rollout and resumes distillation. The authors report that Reframe outperforms Mix-RL and vanilla multi-teacher on-policy distillation across 14 image and video benchmarks, and that no task-specific SFT cold start is needed.
Open the source ↗Similar Research & Safety releases
- InfraRSI: Harnessing Recursive Self-Improvement for Training Infrastructure
InfraRSI Team (Yuchuan Tian, Haocheng Mei, Ye Yuan, Chao Xu, Boxun Li, Guohao Dai, Kai Han; TokenRhythm) · Agentic Training Optimiser · Week 47, 2026
- dNaViT: Discrete Codes are General-Purpose Visual Representations
LongCat team (Xiaotong Li et al.), arXiv · Discrete Visual Tokenizer · Week 47, 2026
- Sage-Taiyi: A Metacognitive Architecture for Scientific Discovery
Shanghai AI Laboratory (Weida Wang et al.) · Metacognitive Co-Scientist · Week 47, 2026
- LongBanana
Kolors Team, Kuaishou Technology (Haoxiang Cao et al.) · Image Synthesis Benchmark · Week 47, 2026
- OneTrans-GSR: A Generative Slate Ranking Paradigm Unifying Reranking and Mix-Ranking with One Autoregressive Transformer
ByteDance (Feng Cheng et al.) · Generative Slate Ranking · Week 47, 2026
- P^2-MOPD: Accelerating Multi-Teacher On-Policy Distillation via Parameter Priors
StepFun (Sinuo Wang et al.) · Parameter-prior distillation · Week 47, 2026
Published by Quanta AI Labs, an AI agency in India. Browse every week in AI News Weekly.