Juan Pino

Artificial Intelligence · 2018–2023

A researcher in the Science corpus: 28 papers; trusts 555 researchers and is trusted by 51 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 723 citations into it; #3,801 of 35,345 by trust here, #2,652 by citations
• Natural Language Processing — 405 citations into it; #2,305 of 5,688 by trust here, #1,955 by citations
• Speech & Audio — 298 citations into it; #284 of 1,076 by trust here, #173 by citations
• Computer Vision and Pattern Recognition — 225 citations into it; #18,412 of 21,575 by trust here, #6,954 by citations
• Signal Processing — 166 citations into it
• Machine Translation — 141 citations into it; #36 of 292 by trust here, #13 by citations
• Evaluation & Benchmarks — 127 citations into it; #1,824 of 3,147 by trust here, #1,212 by citations
• Model Architectures — 90 citations into it

Whom Juan Pino trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Matt Post
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Alex Graves
6. Ilya Sutskever
7. Jimmy Ba
8. Ashish Vaswani
9. Alex Krizhevsky
10. Dzmitry Bahdanau

Who trusts Juan Pino overall

1. Changhan Wang
2. Yun Tang
3. Rong Ye
4. Ye Jia
5. Xian Li
6. Xutai Ma
7. Ann Lee
8. Mingxuan Wang
9. Ankur Bapna
10. Anne Wu

Papers from Juan Pino's perspective

Ordered by how strongly the researchers Juan Pino trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English (2019) — 150 citations
• VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation (2021) — 744 citations
• The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali–English and Sinhala–English (2019) — 250 citations
• XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale (2021) — 1,102 citations
• Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions (2019) — 83 citations
• Fairseq S2T: Fast Speech-to-Text Modeling with Fairseq (2020) — 334 citations
• Direct Speech-to-Speech Translation With Discrete Units (2021) — 241 citations
• Textless Speech-to-Speech Translation on Real Data (2021) — 187 citations
• Large-Scale Self- and Semi-Supervised Learning for Speech Translation (2021) — 49 citations
• Multilingual Speech Translation from Efficient Finetuning of Pretrained Models (2021) — 167 citations
• Lightweight Adapter Tuning for Multilingual Speech Translation (2021) — 98 citations
• Enhanced Direct Speech-to-Speech Translation Using Self-supervised Pre-training and Data Augmentation (2022) — 70 citations
• Self-Supervised Representations Improve End-to-End Speech Translation (2020) — 43 citations
• A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks (2020) — 82 citations
• Improving Speech Translation by Understanding and Learning from the Auxiliary Text Translation Task (2021) — 96 citations
• Self-Training for End-to-End Speech Translation (2020) — 69 citations
• fairseq Sˆ2: A Scalable and Integrable Speech Synthesis Toolkit (2021) — 35 citations
• SIMULEVAL: An Evaluation Toolkit for Simultaneous Translation (2020) — 130 citations
• CoVoST 2: A Massively Multilingual Speech-to-Text Translation Corpus (2020) — 99 citations
• Monotonic Multihead Attention (2019) — 152 citations