Adaptive Collapsing on Bounding Volume Hierarchies for Ray-Tracing. - André Susano Pinto (Eurographics (Short Papers), 2010)

Novelty Detection Using Graphical Models for Semantic Room Classification. - André Susano Pinto; Andrzej Pronobis; Luís Paulo Reis (EPIA, 2011)

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)

In-domain representation learning for remote sensing. - Maxim Neumann; André Susano Pinto; Xiaohua Zhai; Neil Houlsby (CoRR, 2019)

Training General Representations for Remote Sensing Using in-Domain Knowledge. - Maxim Neumann; André Susano Pinto; Xiaohua Zhai; Neil Houlsby (IGARSS, 2020)

Deep Ensembles for Low-Data Transfer Learning. - Basil Mustafa; Carlos Riquelme; Joan Puigcerver; André Susano Pinto; Daniel Keysers; Neil Houlsby (CoRR, 2020)

Scalable Transfer Learning with Expert Models. - Joan Puigcerver; Carlos Riquelme Ruiz; Basil Mustafa; Cédric Renggli; André Susano Pinto; Sylvain Gelly; Daniel Keysers; Neil Houlsby (ICLR, 2021)

Scaling Vision with Sparse Mixture of Experts. - Carlos Riquelme; Joan Puigcerver; Basil Mustafa; Maxim Neumann; Rodolphe Jenatton; André Susano Pinto; Daniel Keysers; Neil Houlsby (NeurIPS, 2021)

Which Model to Transfer? Finding the Needle in the Growing Haystack. - Cédric Renggli; André Susano Pinto; Luka Rimanic; Joan Puigcerver; Carlos Riquelme; Ce Zhang 001; Mario Lucic (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)

Learning to Merge Tokens in Vision Transformers. - Cédric Renggli; André Susano Pinto; Neil Houlsby; Basil Mustafa; Joan Puigcerver; Carlos Riquelme (CoRR, 2022)

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

LocCa: Visual Pretraining with Location-aware Captioners. - Bo Wan; Michael Tschannen; Yongqin Xian; Filip Pavetic; Ibrahim M. Alabdulmohsin; Xiao Wang 038; André Susano Pinto; Andreas Steiner 001; Lucas Beyer; Xiaohua Zhai (NeurIPS, 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)

PaliGemma 2: A Family of Versatile VLMs for Transfer. - Andreas Steiner 001; André Susano Pinto; Michael Tschannen; Daniel Keysers; Xiao Wang 038; Yonatan Bitton; Alexey A. Gritsenko; Matthias Minderer; Anthony Sherbondy; Shangbang Long; Siyang Qin; R. Reeve Ingle; 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)