Paper
Dados & Embeddings
WARP: Weight-Space Analysis for Recovering Training Data Portfolios
WARP is a framework that infers training data compositions from released model weights by analyzing geometric footprints in weight space through model merging and feature extractio…
Hugging Face · Daily Papers
·Tzu-Heng Huang, Aditya Goyal
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·▲ 7 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Tzu-Heng Huang, Aditya Goyal, John Cooper, Frederic Sala
- 7 upvotes da comunidade
- Temas: foundation models, model merging, pseudo-checkpoints, weight space, geometric footprint, geometric features
Resumo
Resumo original (em inglês), extraído do paper:
WARP is a framework that infers training data compositions from released model weights by analyzing geometric footprints in weight space through model merging and feature extraction.