SVs and SIs, various methods have been proposed that exploit structural assumptions or yield probabilistic estimates given limited resources.

Districting is a complex combinatorial problem that consists in partitioning a geographical area into small districts.

We build our dataset from triangu-lated meshes derived from Objaverse-XL and Thingi10K datasets.

We also introduce a metric called Error Residual Ratio (ERR) to better account for varying degrees of label noise.

Recently powerful Large Language Models (LLMs) have become easily accessible to hundreds of millions of users world-wide.

With the success of deep learning, there are growing concerns over interpretability (Lipton, 2018). Ideally, the explanation should be both faithful (reflecting the model's actual behavior) and plausible