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cs.LG2025
Low-Rank Compression of Language Models via Differentiable Rank Selection
Sidhant Sundrani, Francesco Tudisco, Pasquale Minervini
Approaches for compressing large-language models using low-rank decomposition have made strides, particularly with the introduction of activation and loss-aware SVD, which improves…
cs.LG2025
Algebraformer: A Neural Approach to Linear Systems
Pietro Sittoni, Francesco Tudisco
Recent work in deep learning has opened new possibilities for solving classical algorithmic tasks using end-to-end learned models. In this work, we investigate the fundamental task…
cs.LG2024
Subhomogeneous Deep Equilibrium Models
Pietro Sittoni, Francesco Tudisco
Implicit-depth neural networks have grown as powerful alternatives to traditional networks in various applications in recent years. However, these models often lack guarantees of e…