Andrey Zhmoginov

Computer Science · Physical Sciences

18h-index28.4kcitations69works0.32yr avg
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Research Topics

Advanced Neural Network Applications(15), Domain Adaptation and Few-Shot Learning(10), Magnetic confinement fusion research(9), Atomic and Molecular Physics(7), Quantum chaos and dynamical systems(6)

Publications69 total

Projectable Models: One-Shot Generation of Small Specialized Transformers from Large Ones
arXiv (Cornell University)·2025Open Access
Contextually Guided Transformers via Low-Rank Adaptation
arXiv (Cornell University)·2025Open Access
How new data permeates LLM knowledge and how to dilute it
arXiv (Cornell University)·2025· 1 citedOpen Access
Long Context In-Context Compression by Getting to the Gist of Gisting
arXiv (Cornell University)·2025Open Access
Learning and Unlearning of Fabricated Knowledge in Language Models
arXiv (Cornell University)·2024Open Access
MELODI: Exploring Memory Compression for Long Contexts
arXiv (Cornell University)·2024· 1 citedOpen Access
Narrowing the Focus: Learned Optimizers for Pretrained Models
arXiv (Cornell University)·2024Open Access
A kinetic model for pure electron plasma compression via the rotating wall technique
Journal of Plasma Physics·2023Open Access
Decentralized Learning with Multi-Headed Distillation
2023· 5 cited
Continual HyperTransformer: A Meta-Learner for Continual Few-Shot Learning
arXiv (Cornell University)·2023· 5 citedOpen Access
Training trajectories, mini-batch losses and the curious role of the learning rate
arXiv (Cornell University)·2023· 2 citedOpen Access
Transformers learn in-context by gradient descent
arXiv (Cornell University)·2022· 89 citedOpen Access
Decentralized Learning with Multi-Headed Distillation
arXiv (Cornell University)·2022· 1 citedOpen Access
Fine-tuning Image Transformers using Learnable Memory
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)·2022· 49 cited
Fine-tuning Image Transformers using Learnable Memory
arXiv (Cornell University)·2022· 4 citedOpen Access
HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning
arXiv (Cornell University)·2022· 18 citedOpen Access
Compositional Models: Multi-Task Learning and Knowledge Transfer with Modular Networks
arXiv (Cornell University)·2021· 2 citedOpen Access
BasisNet: Two-stage Model Synthesis for Efficient Inference
2021· 5 cited
BasisNet: Two-stage Model Synthesis for Efficient Inference
arXiv (Cornell University)·2021· 1 citedOpen Access
Meta-Learning Bidirectional Update Rules
arXiv (Cornell University)·2021· 2 citedOpen Access
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Frequent Co-authors

M. Sandler(15), J. Fajans(10), Max Vladymyrov(10), Andrew Howard(9), J. S. Wurtele(9), N. J. Fisch(9), F. Robicheaux(8), Mark Sandler(7), A. Capra(7), M. Fujiwara(7), A. Gutiérrez(7), L. L. Kurchaninov(7), J. T. K. McKenna(7), C. So(7), W. Bertsche(6), E. Butler(6), C. L. Cesar(6), M. Charlton(6), S. Eriksson(6), T. Friesen(6)