Max Vladymyrov

Computer Science · Physical Sciences

10h-index749citations29works0.22yr avg
OpenAlex↗Google Scholar↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Face and Expression Recognition(8), Advanced Neural Network Applications(7), Domain Adaptation and Few-Shot Learning(6), Neural Networks and Applications(5), Remote-Sensing Image Classification(4)

Publications29 total

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
Narrowing the Focus: Learned Optimizers for Pretrained Models
arXiv (Cornell University)·2024Open Access
Linear Transformers are Versatile In-Context Learners
arXiv (Cornell University)·2024Open Access
Uncovering mesa-optimization algorithms in Transformers
arXiv (Cornell University)·2023· 5 citedOpen 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
GradMax: Growing Neural Networks using Gradient Information
arXiv (Cornell University)·2022· 9 citedOpen Access
HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning
arXiv (Cornell University)·2022· 18 citedOpen Access
Meta-Learning Bidirectional Update Rules
arXiv (Cornell University)·2021· 2 citedOpen Access
Underspecification Presents Challenges for Credibility in Modern Machine Learning
arXiv (Cornell University)·2020· 430 citedOpen Access
No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms
arXiv (Cornell University)·2019· 1 citedOpen Access
No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms
Neural Information Processing Systems·2019
page 1 of 2Next →

Frequent Co-authors

Andrey Zhmoginov(14), M. Sandler(14), Miguel Á. Carreira-Perpiñán(7), Nolan Miller(7), Johannes von Oswald(3), Gus Kristiansen(3), Eyvind Niklasson(2), João Sacramento(2), Andrew Jackson(2), Blaise Agüera y Arcas(2), Chen Sun(2), Nod Miller(2), Alexander D’Amour(1), Katherine Heller(1), Dan Moldovan(1), Ben Adlam(1), Babak Alipanahi(1), Alex Beutel(1), Christina Chen(1), Jonathan Deaton(1)