Alessandro Favero

According to our database1, Alessandro Favero authored at least 15 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
MEMOIR: Lifelong Model Editing with Minimal Overwrite and Informed Retention for LLMs.
CoRR, June, 2025

Bigger Isn't Always Memorizing: Early Stopping Overparameterized Diffusion Models.
CoRR, May, 2025

Scaling Laws and Representation Learning in Simple Hierarchical Languages: Transformers vs. Convolutional Architectures.
CoRR, May, 2025

How compositional generalization and creativity improve as diffusion models are trained.
CoRR, February, 2025

LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Probing the Latent Hierarchical Structure of Data via Diffusion Models.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
A Phase Transition in Diffusion Models Reveals the Hierarchical Nature of Data.
CoRR, 2024

Multi-Modal Hallucination Control by Visual Information Grounding.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
How Deep Neural Networks Learn Compositional Data: The Random Hierarchy Model.
CoRR, 2023

Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

What Can Be Learnt With Wide Convolutional Neural Networks?
Proceedings of the International Conference on Machine Learning, 2023

2022
How Wide Convolutional Neural Networks Learn Hierarchical Tasks.
CoRR, 2022

2021
Relative stability toward diffeomorphisms in deep nets indicates performance.
CoRR, 2021

Relative stability toward diffeomorphisms indicates performance in deep nets.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Locality defeats the curse of dimensionality in convolutional teacher-student scenarios.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021


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