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Found 3 papers, 2 papers with code
Black-box Adversarial Attacks Against Image Quality Assessment Models
Specifically, we first formulate the attack problem as maximizing the deviation between the estimated quality scores of original and perturbed images, while restricting the perturbed image distortions for visual quality preservation.
Vulnerabilities in Video Quality Assessment Models: The Challenge of Adversarial Attacks
In this paper, we make the first attempt to evaluate the robustness of NR-VQA models against adversarial attacks, and propose a patch-based random search method for black-box attack.
JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs
Existing pre-trained models for knowledge-graph-to-text (KG-to-text) generation simply fine-tune text-to-text pre-trained models such as BART or T5 on KG-to-text datasets, which largely ignore the graph structure during encoding and lack elaborate pre-training tasks to explicitly model graph-text alignments.
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KG-to-Text Generation
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