This intervention significantly improves the performance of LLaMA models on the TruthfulQA benchmark.

Omnidirectional (or 360-degree) images are increasingly being used for 3D applications since they allow the rendering of an entire scene with a single image.

Y et, their massive memory consumption has become a significant roadblock to large-scale training.

In addition, we introduce a simple baseline, "RDumb", that periodically resets the