Gustavo Hernández Ábrego
Artificial Intelligence · 2018–2023
A researcher in the Science corpus: 6 papers; trusts 26 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 212 citations into it; #17,119 of 35,345 by trust here, #3,304 by citations
- Natural Language Processing — 154 citations into it; #3,368 of 5,688 by trust here, #2,069 by citations
- Evaluation & Benchmarks — 68 citations into it
Whom Gustavo Hernández Ábrego trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Noam Shazeer
- Eneko Agirre
- Holger Schwenk
- Daniel Matthew Cer
- Geoffrey E. Hinton
- Yinfei Yang
- Yoshua Bengio
- Ashish Vaswani
- Diederik P. Kingma
- Ilya Sutskever
Who trusts Gustavo Hernández Ábrego overall
- Holger Schwenk
- Shitao Xiao
- Yinfei Yang
- Niklas Muennighoff
- Zhuyun Dai
- Liang Wang
- Paul-Ambroise Duquenne
- Jianmo Ni
- Amin Ahmad
- Jason Baldridge
Papers from Gustavo Hernández Ábrego's perspective
Ordered by how strongly the researchers Gustavo Hernández Ábrego trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
Their papers
- PaLM 2 Technical Report (2023) — 1,524 citations
- Multilingual Universal Sentence Encoder for Semantic Retrieval (2019) — 534 citations
- Effective Parallel Corpus Mining using Bilingual Sentence Embeddings (2018) — 115 citations
- Large Dual Encoders Are Generalizable Retrievers (2021) — 644 citations
- Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax (2019) — 124 citations
- Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models (2021) — 830 citations