30 citations · 43 across the 5 of their papers we have counts for
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cs.CL2021
Control Prefixes for Parameter-Efficient Text Generation
Jordan Clive, Kris Cao, Marek Rei
Prefix-tuning is a powerful lightweight technique for adapting a large pre-trained language model to a downstream application. However, it uses the same dataset-level tuned prompt…
cs.CL2021
You should evaluate your language model on marginal likelihood over tokenisations
Kris Cao, Laura Rimell
Neural language models typically tokenise input text into sub-word units to achieve an open vocabulary. The standard approach is to use a single canonical tokenisation at both trai…
cs.CL2021
Mind the Gap: Assessing Temporal Generalization in Neural Language Models
Angeliki Lazaridou, Adhiguna Kuncoro, Elena Gribovskaya +11
Our world is open-ended, non-stationary, and constantly evolving; thus what we talk about and how we talk about it change over time. This inherent dynamic nature of language contra…