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C. Riquelme

23 papers hereh-index 226.2k citations33 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author17
  • last author2

Across the 23 of 23 papers where every author was matched, so the position is known.

fields
  • cs.LG8
  • cs.CV7
  • stat.ML6
  • cs.SI1
  • hep-th1
same name
  • C. Riquelme — 10 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20142024
most citedPaLI: A Jointly-Scaled Multilingual Language-Image Model

196 citations · 743 across the 22 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.LG2022★ 1 cited

On the Adversarial Robustness of Mixture of Experts

Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme +2

Adversarial robustness is a key desirable property of neural networks. It has been empirically shown to be affected by their sizes, with larger networks being typically more robust…

cs.CV2022★ 196 cited

PaLI: A Jointly-Scaled Multilingual Language-Image Model

Xi Chen, Xiao Wang, Soravit Changpinyo +26

Effective scaling and a flexible task interface enable large language models to excel at many tasks. We present PaLI (Pathways Language and Image model), a model that extends this…

cs.CV2022★ 72 cited

Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts

Basil Mustafa, Carlos Riquelme, Joan Puigcerver +2

Large sparsely-activated models have obtained excellent performance in multiple domains. However, such models are typically trained on a single modality at a time. We present the L…

cs.CV2022★ 24 cited

Learning to Merge Tokens in Vision Transformers

Cedric Renggli, André Susano Pinto, Neil Houlsby +3

Transformers are widely applied to solve natural language understanding and computer vision tasks. While scaling up these architectures leads to improved performance, it often come…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.