Evaluating Durability: Benchmark Insights into Multimodal Watermarking
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Abstract (arXiv)
With the development of large models, watermarks are increasingly employed to assert copyright, verify authenticity, or monitor content distribution. As applications become more multimodal, the utility of watermarking techniques becomes even more critical. The effectiveness and reliability of these watermarks largely depend on their robustness to various disturbances. However, the robustness of these watermarks in real-world scenarios, particularly under perturbations and corruption, is not well understood. To highlight the significance of robustness in watermarking techniques, our study evaluated the robustness of watermarked content generated by image and text generation models against common real-world image corruptions and text perturbations. Our results could pave the way for the development of more robust watermarking techniques in the future. Our project website can be found at urlhttps://mmwatermark-robustness.github.io/.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 69 of its 96 references that are in the map. First posted on arXiv 6 Jun 2024.
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69 of 96 references.
References · 69
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
- 2014Microsoft COCO: Common Objects in Contextcited by 17,608
- 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
- 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
- 2022Generative Adversarial Networkscited by 5,627
- 2023Improved Baselines with Visual Instruction Tuningcited by 4,418
- 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generationcited by 4,322
- 2019Benchmarking Neural Network Robustness to Common Corruptions and Perturbationscited by 2,877
- 2023InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuningcited by 2,876
- 2023MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Modelscited by 2,711
38 more
- 2018ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustnesscited by 1,432
- 2015Spatial Transformer Networkscited by 1,429
- 2020BLEURT: Learning Robust Metrics for Text Generationcited by 1,203
- 2023PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesiscited by 864
- 2023Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inferencecited by 846
- 2023A Watermark for Large Language Modelscited by 725
- 2021SimVLM: Simple Visual Language Model Pretraining with Weak Supervisioncited by 647
- 2018BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentationcited by 645
- 2023NExT-GPT: Any-to-Any Multimodal LLMcited by 615
- 2023mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaborationcited by 547
- 2022LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Actioncited by 439
- 2023Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defensecited by 429
- 2018HiDDeN: Hiding Data With Deep Networkscited by 397
- 2019Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Comingcited by 336
- 2023Robust Distortion-free Watermarks for Language Modelscited by 320
- 2023Provable Robust Watermarking for AI-Generated Textcited by 299
- 2023InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Compositioncited by 297
- 2018Adversarial Example Generation with Syntactically Controlled Paraphrase Networkscited by 286
- 2024SDXL-Lightning: Progressive Adversarial Diffusion Distillationcited by 266
- 2019StegaStamp: Invisible Hyperlinks in Physical Photographscited by 265
- 2017Embedding Watermarks into Deep Neural Networkscited by 248
- 2023Undetectable Watermarks for Language Modelscited by 226
- 2024Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMscited by 224
- 2020Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Datacited by 201
- 2018Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfercited by 191
- 2023On the Reliability of Watermarks for Large Language Modelscited by 189
- 2019Facebook FAIR's WMT19 News Translation Task Submissioncited by 179
- 2019Robust Invisible Video Watermarking with Attentioncited by 149
- 2022Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP)cited by 138
- 2023Invisible Image Watermarks Are Provably Removable Using Generative AIcited by 134
- 2023Kandinsky: an Improved Text-to-Image Synthesis with Image Prior and Latent Diffusioncited by 114
- 2023A Survey of Text Watermarking in the Era of Large Language Modelscited by 112
- 2024WAVES: Benchmarking the Robustness of Image Watermarkscited by 97
- 2021Watermarking Images in Self-Supervised Latent Spacescited by 94
- 2021Learning Compact Metrics for MTcited by 93
- 2020Responsible Disclosure of Generative Models Using Scalable Fingerprintingcited by 91
- 2020Distortion Agnostic Deep Watermarkingcited by 90
- 2023Robustness of AI-Image Detectors: Fundamental Limits and Practical Attackscited by 81
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
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- 2024Robust Watermarking Using Generative Priors Against Image Editing: From Benchmarking to Advances
- 2026What Limits Robustness in Deep Image Watermarking: An Analysis of Mechanisms and Their Scaling Across Capacities ↗
- 2026Watermarking: from Impossibility to Auditable Compliance
- 2026What Breaks Local Watermarks? A Robustness Benchmark for Local Invisible Image Watermarking
- 2026Unforgeable Watermarks for Language Models via Robust Signatures
- 2024Watermark under Fire: A Robustness Evaluation of LLM Watermarking