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cs.LG2024★ 2 cited
Cut Your Losses in Large-Vocabulary Language Models
Erik Wijmans, Brody Huval, Alexander Hertzberg +2
As language models grow ever larger, so do their vocabularies. This has shifted the memory footprint of LLMs during training disproportionately to one single layer: the cross-entro…
cs.LG2018
Assessing Generalization in Deep Reinforcement Learning
Charles Packer, Katelyn Gao, Jernej Kos +3
Deep reinforcement learning (RL) has achieved breakthrough results on many tasks, but agents often fail to generalize beyond the environment they were trained in. As a result, deep…