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ORCIDIbrahim Alabdulmohsin
Ibrahim M. Alabdulmohsin
Person information
- affiliation: Google Research, Zurich, Switzerland
- affiliation (former): King Abdullah University of Science & Technology, Computer, Electrical and Mathematical Sciences & Engineering Division, Thuwal, Saudi Arabia
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2020 – today
- 2025
[i30]Ibrahim Alabdulmohsin, Xiaohua Zhai:
Recursive Inference Scaling: A Winning Path to Scalable Inference in Language and Multimodal Systems. CoRR abs/2502.07503 (2025)- [i29]Xiao Wang, Ibrahim Alabdulmohsin, Daniel Salz, Zhe Li, Keran Rong, Xiaohua Zhai:
Scaling Pre-training to One Hundred Billion Data for Vision Language Models. CoRR abs/2502.07617 (2025) - [i28]Michael Tschannen, Alexey A. Gritsenko, Xiao Wang, Muhammad Ferjad Naeem, Ibrahim Alabdulmohsin, Nikhil Parthasarathy, Talfan Evans, Lucas Beyer, Ye Xia, Basil Mustafa, Olivier J. Hénaff, Jeremiah Harmsen, Andreas Steiner, Xiaohua Zhai:
SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features. CoRR abs/2502.14786 (2025) - [i27]Ibrahim Alabdulmohsin, Andreas Steiner:
A Tale of Two Structures: Do LLMs Capture the Fractal Complexity of Language? CoRR abs/2502.14924 (2025) - 2024
- [c27]Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, A. J. Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut:
On Scaling Up a Multilingual Vision and Language Model. CVPR 2024: 14432-14444 - [c26]Ibrahim Alabdulmohsin, Xiao Wang, Andreas Peter Steiner, Priya Goyal, Alexander D'Amour, Xiaohua Zhai:
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning? ICLR 2024 - [c25]Ibrahim M. Alabdulmohsin, Vinh Q. Tran, Mostafa Dehghani:
Fractal Patterns May Illuminate the Success of Next-Token Prediction. NeurIPS 2024 - [c24]Angéline Pouget, Lucas Beyer, Emanuele Bugliarello, Xiao Wang, Andreas Steiner, Xiaohua Zhai, Ibrahim M. Alabdulmohsin:
No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models. NeurIPS 2024 - [c23]Bo Wan, Michael Tschannen, Yongqin Xian, Filip Pavetic, Ibrahim M. Alabdulmohsin, Xiao Wang, André Susano Pinto, Andreas Steiner, Lucas Beyer, Xiaohua Zhai:
LocCa: Visual Pretraining with Location-aware Captioners. NeurIPS 2024 - [i26]Ibrahim Alabdulmohsin, Vinh Q. Tran, Mostafa Dehghani:
Fractal Patterns May Unravel the Intelligence in Next-Token Prediction. CoRR abs/2402.01825 (2024) - [i25]Ibrahim Alabdulmohsin, Xiao Wang, Andreas Steiner, Priya Goyal, Alexander D'Amour, Xiaohua Zhai:
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning? CoRR abs/2403.04547 (2024) - [i24]Bo Wan, Michael Tschannen, Yongqin Xian, Filip Pavetic, Ibrahim Alabdulmohsin, Xiao Wang, André Susano Pinto, Andreas Steiner, Lucas Beyer, Xiaohua Zhai:
LocCa: Visual Pretraining with Location-aware Captioners. CoRR abs/2403.19596 (2024) - [i23]Angéline Pouget, Lucas Beyer, Emanuele Bugliarello, Xiao Wang, Andreas Peter Steiner, Xiaohua Zhai, Ibrahim Alabdulmohsin:
No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models. CoRR abs/2405.13777 (2024) - [i22]Lucas Beyer, Andreas Steiner, André Susano Pinto, Alexander Kolesnikov, Xiao Wang, Daniel Salz, Maxim Neumann
, Ibrahim Alabdulmohsin, Michael Tschannen, Emanuele Bugliarello, Thomas Unterthiner, Daniel Keysers, Skanda Koppula, Fangyu Liu, Adam Grycner, Alexey A. Gritsenko, Neil Houlsby, Manoj Kumar, Keran Rong, Julian Eisenschlos, Rishabh Kabra, Matthias Bauer, Matko Bosnjak, Xi Chen, Matthias Minderer, Paul Voigtlaender, Ioana Bica, Ivana Balazevic, Joan Puigcerver, Pinelopi Papalampidi, Olivier J. Hénaff, Xi Xiong, Radu Soricut, Jeremiah Harmsen, Xiaohua Zhai:
PaliGemma: A versatile 3B VLM for transfer. CoRR abs/2407.07726 (2024) - [i21]Andreas Steiner, André Susano Pinto, Michael Tschannen, Daniel Keysers, Xiao Wang, Yonatan Bitton, Alexey A. Gritsenko, Matthias Minderer, Anthony Sherbondy, Shangbang Long, Siyang Qin, R. Reeve Ingle, Emanuele Bugliarello, Sahar Kazemzadeh, Thomas Mesnard, Ibrahim Alabdulmohsin, Lucas Beyer, Xiaohua Zhai:
PaliGemma 2: A Family of Versatile VLMs for Transfer. CoRR abs/2412.03555 (2024) - 2023
- [c22]Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai:
Adapting to Latent Subgroup Shifts via Concepts and Proxies. AISTATS 2023: 9637-9661 - [c21]Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic:
FlexiViT: One Model for All Patch Sizes. CVPR 2023: 14496-14506 - [c20]Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby:
Scaling Vision Transformers to 22 Billion Parameters. ICML 2023: 7480-7512 - [c19]Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim M. Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey A. Gritsenko, Mario Lucic, Neil Houlsby:
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. NeurIPS 2023 - [c18]Ibrahim M. Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer:
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design. NeurIPS 2023 - [i20]Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin F. Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Patrick Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby:
Scaling Vision Transformers to 22 Billion Parameters. CoRR abs/2302.05442 (2023) - [i19]Ibrahim Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer:
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design. CoRR abs/2305.13035 (2023) - [i18]Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, A. J. Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut:
PaLI-X: On Scaling up a Multilingual Vision and Language Model. CoRR abs/2305.18565 (2023) - [i17]Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey A. Gritsenko, Mario Lucic, Neil Houlsby:
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. CoRR abs/2307.06304 (2023) - [i16]Xi Chen, Xiao Wang, Lucas Beyer, Alexander Kolesnikov, Jialin Wu, Paul Voigtlaender, Basil Mustafa, Sebastian Goodman, Ibrahim Alabdulmohsin, Piotr Padlewski, Daniel Salz, Xi Xiong, Daniel Vlasic, Filip Pavetic, Keran Rong, Tianli Yu, Daniel Keysers, Xiaohua Zhai, Radu Soricut:
PaLI-3 Vision Language Models: Smaller, Faster, Stronger. CoRR abs/2310.09199 (2023) - 2022
- [c17]Ibrahim M. Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai:
Revisiting Neural Scaling Laws in Language and Vision. NeurIPS 2022 - [c16]Ibrahim M. Alabdulmohsin, Jessica Schrouff, Sanmi Koyejo:
A Reduction to Binary Approach for Debiasing Multiclass Datasets. NeurIPS 2022 - [c15]Jessica Schrouff, Natalie Harris, Sanmi Koyejo, Ibrahim M. Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour:
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings. NeurIPS 2022 - [c14]Alexander Soen, Ibrahim M. Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie:
Fair Wrapping for Black-box Predictions. NeurIPS 2022 - [i15]Alexander Soen, Ibrahim Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie:
Fair Wrapping for Black-box Predictions. CoRR abs/2201.12947 (2022) - [i14]Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour:
Maintaining fairness across distribution shift: do we have viable solutions for real-world applications? CoRR abs/2202.01034 (2022) - [i13]Ibrahim Alabdulmohsin, Jessica Schrouff, Oluwasanmi Koyejo:
A Reduction to Binary Approach for Debiasing Multiclass Datasets. CoRR abs/2205.15860 (2022) - [i12]Ibrahim Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai:
Revisiting Neural Scaling Laws in Language and Vision. CoRR abs/2209.06640 (2022) - [i11]Amr Khalifa, Michael C. Mozer, Hanie Sedghi, Behnam Neyshabur, Ibrahim Alabdulmohsin:
Layer-Stack Temperature Scaling. CoRR abs/2211.10193 (2022) - [i10]Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic:
FlexiViT: One Model for All Patch Sizes. CoRR abs/2212.08013 (2022) - [i9]Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai:
Adapting to Latent Subgroup Shifts via Concepts and Proxies. CoRR abs/2212.11254 (2022) - 2021
- [c13]Ibrahim M. Alabdulmohsin, Mario Lucic:
A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models. NeurIPS 2021: 8072-8084 - [i8]Ibrahim M. Alabdulmohsin:
A Generalization of Classical Formulas in Numerical Integration and Series Convergence Acceleration. CoRR abs/2106.07621 (2021) - [i7]Ibrahim M. Alabdulmohsin, Mario Lucic:
A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models. CoRR abs/2106.12887 (2021) - [i6]Ibrahim M. Alabdulmohsin, Larisa Markeeva, Daniel Keysers, Ilya O. Tolstikhin:
A Generalized Lottery Ticket Hypothesis. CoRR abs/2107.06825 (2021) - [i5]Ibrahim M. Alabdulmohsin, Hartmut Maennel, Daniel Keysers:
The Impact of Reinitialization on Generalization in Convolutional Neural Networks. CoRR abs/2109.00267 (2021) - 2020
- [j2]Ibrahim M. Alabdulmohsin:
Towards a Unified Theory of Learning and Information. Entropy 22(4): 438 (2020) - [c12]Hartmut Maennel, Ibrahim M. Alabdulmohsin, Ilya O. Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers:
What Do Neural Networks Learn When Trained With Random Labels? NeurIPS 2020 - [i4]Ibrahim M. Alabdulmohsin:
Fair Classification via Unconstrained Optimization. CoRR abs/2005.14621 (2020) - [i3]Hartmut Maennel, Ibrahim M. Alabdulmohsin, Ilya O. Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers:
What Do Neural Networks Learn When Trained With Random Labels? CoRR abs/2006.10455 (2020)
2010 – 2019
- 2018
- [c11]Ibrahim M. Alabdulmohsin:
Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization. ICML 2018: 149-158 - [c10]Ibrahim M. Alabdulmohsin:
Axiomatic Characterization of AdaBoost and the Multiplicative Weight Update Procedure. ECML/PKDD (1) 2018: 591-604 - 2017
- [b1]Ibrahim Alabdulmohsin:
Learning via Query Synthesis. King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, 2017 - [c9]Ibrahim M. Alabdulmohsin:
An Information-Theoretic Route from Generalization in Expectation to Generalization in Probability. AISTATS 2017: 92-100 - 2016
- [j1]Ibrahim M. Alabdulmohsin, Moustapha Cissé, Xin Gao, Xiangliang Zhang:
Large margin classification with indefinite similarities. Mach. Learn. 103(2): 215-237 (2016) - [c8]Ibrahim M. Alabdulmohsin, Yufei Han, Yun Shen, Xiangliang Zhang:
Content-Agnostic Malware Detection in Heterogeneous Malicious Distribution Graph. CIKM 2016: 2395-2400 - [c7]Ibrahim M. Alabdulmohsin, Moustapha Cissé, Xiangliang Zhang:
Is Attribute-Based Zero-Shot Learning an Ill-Posed Strategy? ECML/PKDD (1) 2016: 749-760 - [i2]Ibrahim M. Alabdulmohsin:
Uniform Generalization, Concentration, and Adaptive Learning. CoRR abs/1608.06072 (2016) - 2015
- [c6]Ibrahim M. Alabdulmohsin, Xin Gao, Xiangliang Zhang:
Efficient Active Learning of Halfspaces via Query Synthesis. AAAI 2015: 2483-2489 - [c5]Ibrahim M. Alabdulmohsin:
Algorithmic Stability and Uniform Generalization. NIPS 2015: 19-27 - 2014
- [c4]Ibrahim M. Alabdulmohsin, Xin Gao, Xiangliang Zhang:
Support vector machines with indefinite kernels. ACML 2014 - [c3]Ibrahim M. Alabdulmohsin, Xin Gao, Xiangliang Zhang:
Adding Robustness to Support Vector Machines Against Adversarial Reverse Engineering. CIKM 2014: 231-240 - [c2]Ibrahim M. Alabdulmohsin:
Interference in wireless ad hoc networks with smart antennas. IWCMC 2014: 666-671 - [c1]Ibrahim M. Alabdulmohsin, Amal Hyadi, Laila H. Afify, Basem Shihada:
End-to-end delay analysis in wireless sensor networks with service vacation. WCNC 2014: 2799-2804 - [i1]Ibrahim M. Alabdulmohsin:
A Mathematical Theory of Learning. CoRR abs/1405.1513 (2014)
Coauthor Index
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