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Found 3 papers, 2 papers with code
Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data
The proliferation of generative models, combined with pretraining on web-scale data, raises a timely question: what happens when these models are trained on their own generated outputs?
Debating with More Persuasive LLMs Leads to More Truthful Answers
In anticipation of this, we ask: can weaker models assess the correctness of stronger models?
Hierarchical Quantized Autoencoders
Despite progress in training neural networks for lossy image compression, current approaches fail to maintain both perceptual quality and abstract features at very low bitrates.
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