Papers › SimVLM: Simple Visual Language Model Pretraining with Weak Supervision

SimVLM: Simple Visual Language Model Pretraining with Weak Supervision

24 Aug 2021ICLR 2022 4arXiv:2108.10904archive 2025-07-28

ZiRui Wang, Jiahui Yu, Adams Wei Yu, Zihang Dai, Yulia Tsvetkov, Yuan Cao

With recent progress in joint modeling of visual and textual representations, Vision-Language Pretraining (VLP) has achieved impressive performance on many multimodal downstream tasks. However, the requirement for expensive annotations including clean image captions and regional labels limits the scalability of existing approaches, and complicates the pretraining procedure with the introduction of multiple dataset-specific objectives. In this work, we relax these constraints and present a minimalist pretraining framework, named Simple Visual Language Model (SimVLM). Unlike prior work, SimVLM reduces the training complexity by exploiting large-scale weak supervision, and is trained end-to-end with a single prefix language modeling objective. Without utilizing extra data or task-specific customization, the resulting model significantly outperforms previous pretraining methods and achieves new state-of-the-art results on a wide range of discriminative and generative vision-language benchmarks, including VQA (+3.74% vqa-score), NLVR2 (+1.17% accuracy), SNLI-VE (+1.37% accuracy) and image captioning tasks (+10.1% average CIDEr score). Furthermore, we demonstrate that SimVLM acquires strong generalization and transfer ability, enabling zero-shot behavior including open-ended visual question answering and cross-modality transfer.

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FerryHuang/SimVLM mentioned on GitHubpytorch report
yulong-XJTU/SimVLM mentioned on GitHubpytorchMIT report

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Tasks

Image CaptioningLanguage ModelingLanguage ModellingQuestion AnsweringVisual Question AnsweringVisual Question Answering (VQA)

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Image Captioning COCO Captions SimVLM BLEU-4 40.6 #17 of 41 Archive leaderboard report
Image Captioning COCO Captions SimVLM CIDER 143.3 #17 of 41 Archive leaderboard report
Image Captioning COCO Captions SimVLM METEOR 33.4 #17 of 41 Archive leaderboard report
Image Captioning COCO Captions SimVLM SPICE 25.4 #17 of 41 Archive leaderboard report
Image Captioning nocaps entire Single Model B1 83.78 #6 of 39 Archive leaderboard report
Image Captioning nocaps entire Single Model B2 68.86 #6 of 39 Archive leaderboard report
Image Captioning nocaps entire Single Model B3 51.06 #6 of 39 Archive leaderboard report
Image Captioning nocaps entire Single Model B4 32.2 #6 of 39 Archive leaderboard report
Image Captioning nocaps entire Single Model CIDEr 110.31 #6 of 39 Archive leaderboard report
Image Captioning nocaps entire Single Model METEOR 30.55 #6 of 39 Archive leaderboard report
Image Captioning nocaps entire Single Model ROUGE-L 59.86 #6 of 39 Archive leaderboard report
Image Captioning nocaps entire Single Model SPICE 14.49 #6 of 39 Archive leaderboard report
Image Captioning nocaps in-domain Single Model B1 84.64 #7 of 41 Archive leaderboard report
Image Captioning nocaps in-domain Single Model B2 70.0 #7 of 41 Archive leaderboard report
Image Captioning nocaps in-domain Single Model B3 52.96 #7 of 41 Archive leaderboard report
Image Captioning nocaps in-domain Single Model B4 34.66 #7 of 41 Archive leaderboard report
Image Captioning nocaps in-domain Single Model CIDEr 108.98 #7 of 41 Archive leaderboard report
Image Captioning nocaps in-domain Single Model METEOR 31.97 #7 of 41 Archive leaderboard report
Image Captioning nocaps in-domain Single Model ROUGE-L 61.01 #7 of 41 Archive leaderboard report
Image Captioning nocaps in-domain Single Model SPICE 14.6 #7 of 41 Archive leaderboard report
Image Captioning nocaps near-domain Single Model B1 84.36 #6 of 40 Archive leaderboard report
Image Captioning nocaps near-domain Single Model B2 69.83 #6 of 40 Archive leaderboard report
Image Captioning nocaps near-domain Single Model B3 52.42 #6 of 40 Archive leaderboard report
Image Captioning nocaps near-domain Single Model B4 33.74 #6 of 40 Archive leaderboard report
Image Captioning nocaps near-domain Single Model CIDEr 110.76 #6 of 40 Archive leaderboard report
Image Captioning nocaps near-domain Single Model METEOR 30.97 #6 of 40 Archive leaderboard report
Image Captioning nocaps near-domain Single Model ROUGE-L 60.46 #6 of 40 Archive leaderboard report
Image Captioning nocaps near-domain Single Model SPICE 14.61 #6 of 40 Archive leaderboard report
Image Captioning nocaps out-of-domain Single Model B1 80.89 #6 of 40 Archive leaderboard report
Image Captioning nocaps out-of-domain Single Model B2 64.21 #6 of 40 Archive leaderboard report
Image Captioning nocaps out-of-domain Single Model B3 44.38 #6 of 40 Archive leaderboard report
Image Captioning nocaps out-of-domain Single Model B4 24.47 #6 of 40 Archive leaderboard report
Image Captioning nocaps out-of-domain Single Model CIDEr 109.49 #6 of 40 Archive leaderboard report
Image Captioning nocaps out-of-domain Single Model METEOR 27.91 #6 of 40 Archive leaderboard report
Image Captioning nocaps out-of-domain Single Model ROUGE-L 56.69 #6 of 40 Archive leaderboard report
Image Captioning nocaps out-of-domain Single Model SPICE 13.89 #6 of 40 Archive leaderboard report
Image Captioning nocaps-val-in-domain SimVLM CIDEr 113.7 #6 of 11 Archive leaderboard report
Image Captioning nocaps-val-in-domain SimVLM Pre-train (#images) 1.8B #6 of 11 Archive leaderboard report
Image Captioning nocaps-val-in-domain SimVLM SPICE - #6 of 11 Archive leaderboard report
Image Captioning nocaps-val-near-domain SimVLM CIDEr 110.9 #6 of 10 Archive leaderboard report
Image Captioning nocaps-val-near-domain SimVLM Pre-train (#images) 1.8B #6 of 10 Archive leaderboard report
Image Captioning nocaps-val-near-domain SimVLM SPICE - #6 of 10 Archive leaderboard report
Image Captioning nocaps-val-out-domain SimVLM CIDEr 115.2 #5 of 10 Archive leaderboard report
Image Captioning nocaps-val-out-domain SimVLM Pretrain (#images) 1.8B #5 of 10 Archive leaderboard report
Image Captioning nocaps-val-out-domain SimVLM SPICE - #5 of 10 Archive leaderboard report
Image Captioning nocaps-val-overall SimVLM CIDEr 112.2 #6 of 11 Archive leaderboard report
Image Captioning nocaps-val-overall SimVLM Pretrain (#images) 1.8B #6 of 11 Archive leaderboard report
Image Captioning nocaps-val-overall SimVLM SPICE - #6 of 11 Archive leaderboard report
Visual Entailment SNLI-VE test SimVLM Accuracy 86.32 #4 of 8 Archive leaderboard report
Visual Entailment SNLI-VE val SimVLM Accuracy 86.21 #4 of 9 Archive leaderboard report
Visual Question Answering (VQA) VQA v2 test-dev SimVLM Accuracy 80.03 #14 of 56 Archive leaderboard report
Visual Question Answering (VQA) VQA v2 test-std SimVLM overall 80.34 #6 of 38 Archive leaderboard report
Visual Reasoning NLVR2 Dev SimVLM Accuracy 84.53 #8 of 15 Archive leaderboard report
Visual Reasoning NLVR2 Test SimVLM Accuracy 85.15 #7 of 14 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

Introduced by this paper: SimVLM

SimVLM

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