SLOT adapts an LLM to each prompt by optimizing a lightweight final-layer vector to minimize prompt loss, boosting benchmark reasoning accuracy by a few points.
Test-time training can close the natural distribution shift performance gap in deep learning based compressed sensing
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SLOT: Sample-specific Language Model Optimization at Test-time
SLOT adapts an LLM to each prompt by optimizing a lightweight final-layer vector to minimize prompt loss, boosting benchmark reasoning accuracy by a few points.