LCDD creates sparse carriers for SFT behaviors that SFT-Eraser can reverse, with ablations showing the sparse structure enables causal control.
Learning sparse neural net- works throughl 0regularization.arXiv preprint arXiv:1712.01312
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
Light-FMP prunes features and model parameters in deep recommender systems by pretraining a hard-concrete masking layer on data subsets, then retraining the reduced model to improve both efficiency and accuracy over prior methods.
paFEMU enables rapid constitutive model discovery by integrating sparse regression, physics augmentation, and finite element adjoint optimization on multi-modal data for interpretable transfer learning.
citing papers explorer
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Crafting Reversible SFT Behaviors in Large Language Models
LCDD creates sparse carriers for SFT behaviors that SFT-Eraser can reverse, with ablations showing the sparse structure enables causal control.
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Light-FMP: Lightweight Feature and Model Pruning for Enhanced Deep Recommender Systems
Light-FMP prunes features and model parameters in deep recommender systems by pretraining a hard-concrete masking layer on data subsets, then retraining the reduced model to improve both efficiency and accuracy over prior methods.
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Towards Rapid Constitutive Model Discovery from Multi-Modal Data: Physics Augmented Finite Element Model Updating (paFEMU)
paFEMU enables rapid constitutive model discovery by integrating sparse regression, physics augmentation, and finite element adjoint optimization on multi-modal data for interpretable transfer learning.