Browse PQC-verified AI models, datasets, and tools
PURGE: Partition-Aware Unlearning for Removing Spurious-Correlation Generated Errors PURGE is a partitioning strategy applied to existing public datasets (MSCOCO 2017) that separates object-relevant evidence from spurious background cues in LVLMs. This repository hosts the resulting preprocessed retain/forget partitions for direct reuse. NeurIPS 2026 Evaluations & Datasets Track, Submission #2701. Hosted under an anonymous account for double-blind review; will be transferred… See the full description on the dataset page: https://huggingface.co/datasets/anonnnnnsub/neuripsED_2701.