Neural Radiance Field (NeRF) is an implicit 3D reconstruction method that has shown immense potential and has gained significant attention for its ability to reconstruct 3D scenes solely from a set of photographs.

Fine-tuning pre-trained models is a popular approach in machine learning for solving complex tasks with moderate data.

In this work, we study the low-rank MDPs with adversarially changed losses in the full-information feedback setting.