Luca Zancato

According to our database¹, Luca Zancato authored at least 29 papers between 2020 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Links

On csauthors.net:

Bibliography

2026

Priming: Hybrid State Space Models From Pre-trained Transformers.

[BibT_eX]

[DOI]

CoRR, May, 2026

Learning When to Attend: Conditional Memory Access for Long-Context LLMs.

[BibT_eX]

[DOI]

CoRR, March, 2026

2025

Gated KalmaNet: A Fading Memory Layer Through Test-Time Ridge Regression.

[BibT_eX]

[DOI]

CoRR, November, 2025

Maximally-Informative Retrieval for State Space Model Generation.

[BibT_eX]

[DOI]

CoRR, June, 2025

Descriminative-Generative Custom Tokens for Vision-Language Models.

[BibT_eX]

[DOI]

CoRR, February, 2025

LC-PLM: Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2025

Expansion Span: Combining Fading Memory and Retrieval in Hybrid State Space Models.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Neuro-symbolic Systems, 2025

Marconi: Prefix Caching for the Era of Hybrid LLMs.

[BibT_eX]

[DOI]

Proceedings of the Eighth Conference on Machine Learning and Systems, 2025

PICASO: Permutation-Invariant Context Composition with State Space Models.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Long-context Protein Language Model.

[BibT_eX]

[DOI]

CoRR, 2024

Compositional Structures in Neural Embedding and Interaction Decompositions.

[BibT_eX]

[DOI]

CoRR, 2024

B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Meaning Representations from Trajectories in Autoregressive Models.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

SemiGPC: Distribution-Aware Label Refinement for Imbalanced Semi-Supervised Learning Using Gaussian Processes.

[BibT_eX]

[DOI]

Abdelhak Lemkhenter

Manchen Wang

Luca Zancato

Gurumurthy Swaminathan

Paolo Favaro

Davide Modolo

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

CPR: Retrieval Augmented Generation for Copyright Protection.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Multi-Modal Hallucination Control by Visual Information Grounding.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Prompt Algebra for Task Composition.

[BibT_eX]

[DOI]

CoRR, 2023

Introspective Cross-Attention Probing for Lightweight Transfer of Pre-trained Models.

[BibT_eX]

[DOI]

CoRR, 2023

Linear Spaces of Meanings: the Compositional Language of VLMs.

[BibT_eX]

[DOI]

CoRR, 2023

Leveraging sparse and shared feature activations for disentangled representation learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Your representations are in the network: composable and parallel adaptation for large scale models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Linear Spaces of Meanings: Compositional Structures in Vision-Language Models.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Train/Test-Time Adaptation with Retrieval.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

À-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable Prompting.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Stacked Residuals of Dynamic Layers for Time Series Anomaly Detection.

[BibT_eX]

[DOI]

CoRR, 2022

Sampling matters: SGD smoothing through importance sampling.

[BibT_eX]

[DOI]

Luca Zancato

Alessandro Chiuso

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021

A novel Deep Neural Network architecture for non-linear system identification.

[BibT_eX]

[DOI]

Luca Zancato

Alessandro Chiuso

CoRR, 2021

A linearized framework and a new benchmark for model selection for fine-tuning.

[BibT_eX]

[DOI]

CoRR, 2021

2020

Predicting Training Time Without Training.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Luca Zancato

Timeline

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Links

On csauthors.net:

Bibliography

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