Key Aspects of Test-Time Training for LLMs

Test-time training involves temporarily updating the model’s parameters during inference using a loss function derived from the input data. The process typically follows these steps:

* Start with the initial model parameters.
* Generate training data from the test input.
* Optimize the model parameters to minimize a loss function on this generated data.
* Use the updated parameters to make predictions on the test input.
* Restore the original parameters for the next test instance1
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