Learning At Test Time: RNNs With Expressive Hidden States
New RNN model "Learning to (Learn at Test Time)" adapts & learns during test time with dynamic hidden state updates via TTT layers, outperforming standard RNNs on benchmark tasks.
This is a Plain English Papers summary of a research paper called Learning to (Learn at Test Time): RNNs with Expressive Hidden States. If you like these kinds of analysis, you should subscribe to the AImodels.fyi newsletter or follow me on Twitter. Overview This paper introduces a new type of recurrent neural network (RNN) called "Learning to (Learn at Test Time)" (LTLTT) that can learn and adapt during test time. The LTLTT model uses "TTT layers" that can dynamically update the RNN's hidden state to improve performance on new tasks or data. The paper demonstrates the LTLTT model's...