mlsanityData to 14 Oct 2026

Evaluating Durability: Benchmark Insights into Multimodal Watermarking

arXiv 2406.03728 ↗First posted 6 Jun 2024cs.CVcited by 3

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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.

Builds on

69 of 96 references.

References · 69

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38 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025VideoMarkBench: Benchmarking Robustness of Video Watermarking
  2. 2024Certifiably Robust Image Watermark
  3. 2024Robust Watermarking Using Generative Priors Against Image Editing: From Benchmarking to Advances
  4. 2026What Limits Robustness in Deep Image Watermarking: An Analysis of Mechanisms and Their Scaling Across Capacities ↗
  5. 2026Watermarking: from Impossibility to Auditable Compliance
  6. 2026What Breaks Local Watermarks? A Robustness Benchmark for Local Invisible Image Watermarking
  7. 2026Unforgeable Watermarks for Language Models via Robust Signatures
  8. 2024Watermark under Fire: A Robustness Evaluation of LLM Watermarking