{"data":{"full_name":"vbercy/g2tm-segmenter","name":"g2tm-segmenter","description":"Graph-Guided Token Merging (G2TM) is a lightweight one-shot module designed to eliminate redundant tokens early in the ViT architecture. It performs a single merging step after a shallow attention block, enabling all subsequent layers to operate on a compact token set. It leverages graph theory to identify groups of semantically redundant patches.","stars":2.0,"forks":0.0,"language":"Python","license":"Apache-2.0","archived":0.0,"subcategory":"graph-neural-networks","last_pushed_at":"2026-03-20T08:55:21+00:00","pypi_package":null,"npm_package":null,"downloads_monthly":0.0,"dependency_count":0.0,"commits_30d":null,"reverse_dep_count":0.0,"maintenance_score":13.0,"adoption_score":2.0,"maturity_score":9.0,"community_score":0.0,"quality_score":24.0,"quality_tier":"experimental","risk_flags":"['no_package', 'no_dependents']"},"meta":{"timestamp":"2026-04-07T10:32:36.175910+00:00"}}