Researchmultimodal llmfine grained visionchain of thoughtfew shot
Fine-R1 Delivers Few-Shot Fine-Grained Visual Recognition
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8.0
Researchers post an arXiv preprint on Feb 7, 2026 introducing Fine-R1, a multimodal large language model tailored for fine-grained visual recognition using Chain-of-Thought supervised fine-tuning and Triplet Augmented Policy Optimization. With only 4-shot training, the model reportedly outperforms general MLLMs and contrastive CLIP models on seen and unseen sub-categories, improving robustness to intra-class variance and discriminative ability; code is available.
Scoring Rationale
Strong methodological novelty and few-shot results drive score; limited by single arXiv preprint without peer review.
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