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Found 5 papers, 2 papers with code
Rethinking Artistic Copyright Infringements in the Era of Text-to-Image Generative Models
Recent text-to-image generative models such as Stable Diffusion are extremely adept at mimicking and generating copyrighted content, raising concerns amongst artists that their unique styles may be improperly copied.
Can AI-Generated Text be Reliably Detected?
In particular, we develop a recursive paraphrasing attack to apply on AI text, which can break a whole range of detectors, including the ones using the watermarking schemes as well as neural network-based detectors, zero-shot classifiers, and retrieval-based detectors.
Towards Improved Input Masking for Convolutional Neural Networks
In this work, we propose a new masking method for CNNs we call layer masking in which the missingness bias caused by masking is reduced to a large extent.
Simulating Network Paths with Recurrent Buffering Units
Simulating physical network paths (e. g., Internet) is a cornerstone research problem in the emerging sub-field of AI-for-networking.
What's in a Name? Are BERT Named Entity Representations just as Good for any other Name?
We evaluate named entity representations of BERT-based NLP models by investigating their robustness to replacements from the same typed class in the input.
