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cs.LG2026
Learning Generation Orders for Masked Discrete Diffusion Models via Variational Inference
David Fox, Sam Bowyer, Song Liu +3
Masked discrete diffusion models (MDMs) are a promising new approach to generative modelling, offering the ability for parallel token generation and therefore greater efficiency th…
cs.LG2025
Controlling changes to attention logits
Ben Anson, Laurence Aitchison
Stability of neural network weights is critical when training transformer models. The query and key weights are particularly problematic, as they tend to grow large without any int…
cs.LG2024
Questionable practices in machine learning
Gavin Leech, Juan J. Vazquez, Niclas Kupper +2
Evaluating modern ML models is hard. The strong incentive for researchers and companies to report a state-of-the-art result on some metric often leads to questionable research prac…