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Memory evolution may outshine test-time training in science tasks
What is Can Test-Time Memory Evolution Outperform Test-Time Training for Scientific Discovery??
A new study shows that updating a model’s memory at inference time can match or beat the performance of full test-time training, while avoiding the heavy compute cost of online weight updates. The approach keeps the model weights fixed and instead evolves an external memory store during discovery.
Who it is for
Anyone building scientific discovery pipelines with LLMs can boost accuracy without the extra compute overhead of test-time training.