Closed-Form Approximate CRF Training for Scalable Image Segmentation. - Alexander Kolesnikov 003; Matthieu Guillaumin; Vittorio Ferrari; Christoph H. Lampert (ECCV (3), 2014)

Closed-Form Training of Conditional Random Fields for Large Scale Image Segmentation. - Alexander Kolesnikov 003; Matthieu Guillaumin; Vittorio Ferrari; Christoph H. Lampert (CoRR, 2014)

Identifying Reliable Annotations for Large Scale Image Segmentation. - Alexander Kolesnikov 003; Christoph H. Lampert (CoRR, 2015)

Improving Weakly-Supervised Object Localization By Micro-Annotation. - Alexander Kolesnikov 003; Christoph H. Lampert (BMVC, 2016)

Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. - Alexander Kolesnikov 003; Christoph H. Lampert (ECCV (4), 2016)

Deep Probabilistic Modeling of Natural Images using a Pyramid Decomposition. - Alexander Kolesnikov 003; Christoph H. Lampert (CoRR, 2016)

iCaRL: Incremental Classifier and Representation Learning. - Sylvestre-Alvise Rebuffi; Alexander Kolesnikov 003; Christoph H. Lampert (CoRR, 2016)

Probabilistic Image Colorization. - Amelie Royer; Alexander Kolesnikov 003; Christoph H. Lampert (BMVC, 2017)

iCaRL: Incremental Classifier and Representation Learning. - Sylvestre-Alvise Rebuffi; Alexander Kolesnikov 003; Georg Sperl; Christoph H. Lampert (CVPR, 2017)

PixelCNN Models with Auxiliary Variables for Natural Image Modeling. - Alexander Kolesnikov 003; Christoph H. Lampert (ICML, 2017)

Detecting Visual Relationships Using Box Attention. - Alexander Kolesnikov 003; Christoph H. Lampert; Vittorio Ferrari (CoRR, 2018)

Revisiting Self-Supervised Visual Representation Learning. - Alexander Kolesnikov 003; Xiaohua Zhai; Lucas Beyer (CVPR, 2019)

S4L: Self-Supervised Semi-Supervised Learning. - Lucas Beyer; Xiaohua Zhai; Avital Oliver; Alexander Kolesnikov 003 (ICCV, 2019)

Detecting Visual Relationships Using Box Attention. - Alexander Kolesnikov 003; Alina Kuznetsova; Christoph Lampert; Vittorio Ferrari (ICCV Workshops, 2019)

S4L: Self-Supervised Semi-Supervised Learning. - Xiaohua Zhai; Avital Oliver; Alexander Kolesnikov 003; Lucas Beyer (CoRR, 2019)

The Visual Task Adaptation Benchmark. - Xiaohua Zhai; Joan Puigcerver; Alexander Kolesnikov 003; Pierre Ruyssen; Carlos Riquelme; Mario Lucic; Josip Djolonga; André Susano Pinto; Maxim Neumann; Alexey Dosovitskiy; Lucas Beyer; Olivier Bachem; et al. (CoRR, 2019)

Large Scale Learning of General Visual Representations for Transfer. - Alexander Kolesnikov 003; Lucas Beyer; Xiaohua Zhai; Joan Puigcerver; Jessica Yung; Sylvain Gelly; Neil Houlsby (CoRR, 2019)

Big Transfer (BiT): General Visual Representation Learning. - Alexander Kolesnikov 003; Lucas Beyer; Xiaohua Zhai; Joan Puigcerver; Jessica Yung; Sylvain Gelly; Neil Houlsby (ECCV (5), 2020)

Are we done with ImageNet? - Lucas Beyer; Olivier J. Hénaff; Alexander Kolesnikov 003; Xiaohua Zhai; Aäron van den Oord (CoRR, 2020)

The Open Images Dataset V4. - Alina Kuznetsova; Hassan Rom; Neil Alldrin; Jasper R. R. Uijlings; Ivan Krasin; Jordi Pont-Tuset; Shahab Kamali; Stefan Popov; Matteo Malloci; Alexander Kolesnikov 003; Tom Duerig; Vittorio Ferrari (Int. J. Comput. Vis., 2020)

On Robustness and Transferability of Convolutional Neural Networks. - Josip Djolonga; Jessica Yung; Michael Tschannen; Rob Romijnders; Lucas Beyer; Alexander Kolesnikov 003; Joan Puigcerver; Matthias Minderer; Alexander D'Amour; Dan Moldovan; Sylvain Gelly; Neil Houlsby; et al. (CVPR, 2021)

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. - Alexey Dosovitskiy; Lucas Beyer; Alexander Kolesnikov 003; Dirk Weissenborn; Xiaohua Zhai; Thomas Unterthiner; Mostafa Dehghani 001; Matthias Minderer; Georg Heigold; Sylvain Gelly; Jakob Uszkoreit; Neil Houlsby (ICLR, 2021)

MLP-Mixer: An all-MLP Architecture for Vision. - Ilya O. Tolstikhin; Neil Houlsby; Alexander Kolesnikov 003; Lucas Beyer; Xiaohua Zhai; Thomas Unterthiner; Jessica Yung; Andreas Steiner 001; Daniel Keysers; Jakob Uszkoreit; Mario Lucic; Alexey Dosovitskiy (NeurIPS, 2021)

SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size. - Jessica Yung; Rob Romijnders; Alexander Kolesnikov 003; Lucas Beyer; Josip Djolonga; Neil Houlsby; Sylvain Gelly; Mario Lucic; Xiaohua Zhai (CoRR, 2021)

Knowledge distillation: A good teacher is patient and consistent. - Lucas Beyer; Xiaohua Zhai; Amélie Royer; Larisa Markeeva; Rohan Anil; Alexander Kolesnikov 003 (CVPR, 2022)

Scaling Vision Transformers. - Xiaohua Zhai; Alexander Kolesnikov 003; Neil Houlsby; Lucas Beyer (CVPR, 2022)

LiT: Zero-Shot Transfer with Locked-image text Tuning. - Xiaohua Zhai; Xiao Wang 038; Basil Mustafa; Andreas Steiner 001; Daniel Keysers; Alexander Kolesnikov 003; Lucas Beyer (CVPR, 2022)

UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes. - Alexander Kolesnikov 003; André Susano Pinto; Lucas Beyer; Xiaohua Zhai; Jeremiah Harmsen; Neil Houlsby (NeurIPS, 2022)

Better plain ViT baselines for ImageNet-1k. - Lucas Beyer; Xiaohua Zhai; Alexander Kolesnikov 003 (CoRR, 2022)

PaLI: A Jointly-Scaled Multilingual Language-Image Model. - Xi Chen 071; Xiao Wang 038; Soravit Changpinyo; A. J. Piergiovanni; Piotr Padlewski; Daniel Salz; Sebastian Goodman; Adam Grycner; Basil Mustafa; Lucas Beyer; Alexander Kolesnikov 003; Joan Puigcerver; et al. (CoRR, 2022)

How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers. - Andreas Steiner 001; Alexander Kolesnikov 003; Xiaohua Zhai; Ross Wightman; Jakob Uszkoreit; Lucas Beyer (Trans. Mach. Learn. Res., 2022)

FlexiViT: One Model for All Patch Sizes. - Lucas Beyer; Pavel Izmailov; Alexander Kolesnikov 003; Mathilde Caron; Simon Kornblith; Xiaohua Zhai; Matthias Minderer; Michael Tschannen; Ibrahim Alabdulmohsin; Filip Pavetic (CVPR, 2023)

Sigmoid Loss for Language Image Pre-Training. - Xiaohua Zhai; Basil Mustafa; Alexander Kolesnikov 003; Lucas Beyer (ICCV, 2023)

PaLI: A Jointly-Scaled Multilingual Language-Image Model. - Xi Chen 071; Xiao Wang 038; Soravit Changpinyo; A. J. Piergiovanni; Piotr Padlewski; Daniel Salz; Sebastian Goodman; Adam Grycner; Basil Mustafa; Lucas Beyer; Alexander Kolesnikov 003; Joan Puigcerver; et al. (ICLR, 2023)

Scaling Vision Transformers to 22 Billion Parameters. - Mostafa Dehghani 001; Josip Djolonga; Basil Mustafa; Piotr Padlewski; Jonathan Heek; Justin Gilmer; Andreas Peter Steiner; Mathilde Caron; Robert Geirhos; Ibrahim Alabdulmohsin; Rodolphe Jenatton; Lucas Beyer; et al. (ICML, 2023)

Tuning Computer Vision Models With Task Rewards. - André Susano Pinto; Alexander Kolesnikov 003; Yuge Shi; Lucas Beyer; Xiaohua Zhai (ICML, 2023)

Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design. - Ibrahim M. Alabdulmohsin; Xiaohua Zhai; Alexander Kolesnikov 003; Lucas Beyer (NeurIPS, 2023)

A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision. - Lucas Beyer; Bo Wan; Gagan Madan; Filip Pavetic; Andreas Steiner 001; Alexander Kolesnikov 003; André Susano Pinto; Emanuele Bugliarello; Xiao Wang 038; Qihang Yu; Liang-Chieh Chen; Xiaohua Zhai (CoRR, 2023)

PaLI-X: On Scaling up a Multilingual Vision and Language Model. - Xi Chen 071; Josip Djolonga; Piotr Padlewski; Basil Mustafa; Soravit Changpinyo; Jialin Wu; Carlos Riquelme Ruiz; Sebastian Goodman; Xiao Wang 038; Yi Tay; Siamak Shakeri; Mostafa Dehghani 001; et al. (CoRR, 2023)

PaLI-3 Vision Language Models: Smaller, Faster, Stronger. - Xi Chen 071; Xiao Wang 038; Lucas Beyer; Alexander Kolesnikov 003; Jialin Wu; Paul Voigtlaender; Basil Mustafa; Sebastian Goodman; Ibrahim Alabdulmohsin; Piotr Padlewski; Daniel Salz; Xi Xiong; et al. (CoRR, 2023)

On Scaling Up a Multilingual Vision and Language Model. - Xi Chen 071; Josip Djolonga; Piotr Padlewski; Basil Mustafa; Soravit Changpinyo; Jialin Wu; Carlos Riquelme Ruiz; Sebastian Goodman; Xiao Wang 038; Yi Tay; Siamak Shakeri; Mostafa Dehghani 001; et al. (CVPR, 2024)

Toward a Diffusion-Based Generalist for Dense Vision Tasks. - Yue Fan; Yongqin Xian; Xiaohua Zhai; Alexander Kolesnikov 003; Muhammad Ferjad Naeem; Bernt Schiele; Federico Tombari (CoRR, 2024)

PaliGemma: A versatile 3B VLM for transfer. - Lucas Beyer; Andreas Steiner 001; André Susano Pinto; Alexander Kolesnikov 003; Xiao Wang 038; Daniel Salz; Maxim Neumann; Ibrahim Alabdulmohsin; Michael Tschannen; Emanuele Bugliarello; Thomas Unterthiner; Daniel Keysers; et al. (CoRR, 2024)

JetFormer: An autoregressive generative model of raw images and text. - Michael Tschannen; André Susano Pinto; Alexander Kolesnikov 003 (ICLR, 2025)

Jet: A Modern Transformer-Based Normalizing Flow. - Alexander Kolesnikov 003; André Susano Pinto; Michael Tschannen (Trans. Mach. Learn. Res., 2025)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)