Mixture-of-experts (MoE) transformers, the standard backbone for modern large-scale deep learning, employ conditional computation: only a sparse subset of model weights is used in each forward pass. I
Mixture-of-experts (MoE) transformers, the standard backbone for modern large-scale deep learning, employ conditional computation: only a sparse subset of model weights is used in each forward pass. I
Details from Hugging Face ↗.
Nested Sparsity for Scalable Pretraining and Continual Learning was first seen on Hugging Face · Daily papers on Oct 27, 2026. Since then it has appeared in 3 checks on 2 different days. Its best position was #27 of 30, reached on Oct 28, 01:28 UTC. It dropped off the list after Oct 28, 01:28 UTC.
Position on Hugging Face · Daily papers at every check (lower is better).
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Not at the moment. It was last on the list on Oct 28, 01:28 UTC, after 2 days of trending.
#27 on Hugging Face · Daily papers, on Oct 28, 01:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Oct 27, 2026 and has been on the list on 2 days (3 checks) since.