Luca Zancato
12 papers · 2020–2026 · 4 venues · across top CS/AI venues
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Machine Learning
(9)
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(6)
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(4)
Learning Types Β· Deep Learning
(4)
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(2)
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(2)
Computer Vision
(1)
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(1)
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(1)
Keywords
state space model
(3)
vision-language model
(2)
transfer learning
(2)
contrastive learning
(1)
zero-shot learning
(1)
vision transformer
(1)
stochastic gradient descent
(1)
feature learning
(1)
image generation
(1)
autoregressive generation
(1)
domain adaptation
(1)
embedding space
(1)
direct preference optimization
(1)
self-supervised learning
(1)
information retrieval
(1)
multi-task learning
(1)
ridge regression
(1)
test-time adaptation
(1)
privacy preservation
(1)
continual learning
(1)
Papers
Gated KalmaNet: A Fading Memory Layer through Test-time Ridge Regression
CVPR 2026
PICASO: Permutation-Invariant Context Composition with State Space Models
ICLR 2025
B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory
NeurIPS 2024
CPR: Retrieval Augmented Generation for Copyright Protection
CVPR 2024
Meaning Representations from Trajectories in Autoregressive Models
ICLR 2024
Multi-Modal Hallucination Control by Visual Information Grounding
CVPR 2024
A-La-Carte Prompt Tuning (APT): Combining Distinct Data via Composable Prompting
CVPR 2023
Leveraging sparse and shared feature activations for disentangled representation learning
NeurIPS 2023
Linear Spaces of Meanings: Compositional Structures in Vision-Language Models
ICCV 2023
Train/Test-Time Adaptation With Retrieval
CVPR 2023
Your representations are in the network: composable and parallel adaptation for large scale models
NeurIPS 2023
Predicting Training Time Without Training
NeurIPS 2020