Publications

FlowTSE: Target Speaker Extraction with Flow Matching
A. Navon, A. Shamsian, Y. Segal-Feldman, N. Glazer, G. Hetz, J. Keshet
Conference of the International Speech Communication Association (InterSpeech 2025).
[paper] [demo]

Whisper in Medusa’s Ear: Multi-head Efficient Decoding for Transformer-based ASR
Y. Segal-Feldman, A. Shamsian, A. Navon, G. Hetz, J. Keshet
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2025).
[paper] [code] [blog] [demo]

Keyword-Guided Adaptation of Automatic Speech Recognition
A. Shamsian, A. Navon, N. Glazer, G. Hetz, J. Keshet
Conference of the International Speech Communication Association (InterSpeech 2024).
[paper]

Equivariant Deep Weight Space Alignment
A. Navon, A. Shamsian, E. Fetaya, G. Chechik, N. Dym, H. Maron
International Conference on Machine Learning, ICML, 2024.
[paper]

Improved Generalization of Weight Space Networks via Augmentations
A. Shamsian, A. Navon, D. Zhang, Y. Zhang, E. Fetaya, G. Chechik, H. Maron
International Conference on Machine Learning, ICML, 2024.
[paper]

Open-vocabulary Keyword-spotting with Adaptive Instance Normalization
A. Navon, A. Shamsian, N. Glazer, G. Hetz, J. Keshet
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024).
[paper]

Equivariant Architectures for Learning in Deep Weight Spaces
A. Navon, A. Shamsian, I. Achituve, E. Fetaya, G. Chechik, H. Maron
International Conference on Machine Learning, ICML, 2023.
Oral presentation.
[paper] [project page] [video] [poster] [code] [blog] [bibtex]

Auxiliary Learning as an Asymmetric Bargaining Game
A. Shamsian, A. Navon, N. Glazer, K. Kawaguchi, G. Chechik, E. Fetaya
International Conference on Machine Learning, ICML, 2023.
[paper] [project page] [code] [bibtex]

Multi-Task Learning as a Bargaining Game
A. Navon, A. Shamsian, I. Achituve, H. Maron, K. Kawaguchi, G. Chechik, E. Fetaya
International Conference on Machine Learning, ICML, 2022.
[paper] [project page] [video] [poster] [code] [bibtex]

Personalized Federated Learning using Hypernetworks
A. Shamsian, A. Navon, G. Chechik, E. Fetaya
International Conference on Machine Learning, ICML, 2021.
Personalized Federated Learning using Hypernetworks.
ICML, 2021.
[paper] [project page] [code] [bibtex]

Personalized Federated Learning with Gaussian Processes
I. Achituve, A. Shamsian, A. Navon, G. Chechik, E. Fetaya
Neural Information Processing Systems, NeurIPS 2021.
[paper] [code]

GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning
I. Achituve, A. Navon, Y. Yemini, G. Chechik, E. Fetaya
International Conference on Machine Learning, ICML 2021.
[paper] [bibtex]

Learning the Pareto Front with Hypernetworks
A. Navon, A. Shamsian, G. Chechik, E. Fetaya
International Conference on Learning Representations, ICLR 2021.
[paper] [project page] [video] [poster] [code] [bibtex]

Auxiliary Learning by Implicit Differentiation
A. Navon, I. Achituve, H. Maron, G. Chechik, E. Fetaya
International Conference on Learning Representations, ICLR 2021.
[paper] [project page] [video] [poster] [code] [bibtex]

Capturing Between-Tasks Covariance and Similarities Using Multivariate Linear Mixed Models
A. Navon, S. Rosset
Electronic Journal of Statistics, EJS 2020.
[paper] [code] [bibtex]

Preprints

Go Beyond Your Means: Unlearning with Per-Sample Gradient Orthogonalization
A. Shamsian, E. Shaar, A. Navon, G. Chechik, E. Fetaya
Preprint, 2025.

WhisperNER: Unified Open Named Entity and Speech Recognition
G. Ayache, M. Pirchi, A. Navon, A. Shamsian, G. Hetz, J. Keshet
Preprint, 2024.
[paper] [code] [demo] [models]

Learning Discrete Weights and Activations Using the Local Reparameterization Trick
G. Berger, A. Navon, E. Fetaya
Preprint, 2023.

A Study on the Evaluation of Generative Models
E. Betzalel, C. Penso, A. Navon, E. Fetaya
Preprint, 2022.