Cristian Canton Ferrer
Artificial Intelligence · with Wang · 2020–2024
A researcher in the Science corpus: 7 papers; trusts 28 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 235 citations into it
- Computer Vision and Pattern Recognition — 99 citations into it
- Model Architectures — 22 citations into it
Whom Cristian Canton Ferrer trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Diederik P. Kingma
- Ross B. Girshick
- Ilya Sutskever
- Yann LeCun
- Alex Graves
- Tomas Mikolov
Papers from Cristian Canton Ferrer's perspective
Ordered by how strongly the researchers Cristian Canton Ferrer trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Llama 2: Open Foundation and Fine-Tuned Chat Models (2023) — 17,670 citations
- Towards Measuring Fairness in AI: The Casual Conversations Dataset (2021) — 123 citations
- Code Llama: Open Foundation Models for Code (2023) — 3,394 citations
- Preserving integrity in online social networks (2020) — 64 citations
- The Llama 3 Herd of Models (2024) — 17,085 citations
- When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards (2024) — 153 citations
- The DeepFake Detection Challenge (DFDC) Dataset. (2020) — 951 citations