Adam Lopez

Artificial Intelligence · 2010–2020

A researcher in the Science corpus: 8 papers; trusts 136 researchers and is trusted by 43 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 115 citations into it; #17,849 of 35,345 by trust here, #10,319 by citations
• Natural Language Processing — 101 citations into it; #1,071 of 5,688 by trust here, #1,351 by citations
• Safety, Robustness & Interpretability — 26 citations into it
• Representation & Self-Supervised Learning — 24 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Evaluation & Benchmarks — 17 citations into it; #867 of 3,147 by trust here, #2,853 by citations
• Model Architectures — 15 citations into it
• Signal Processing — 10 citations into it

Whom Adam Lopez trusts overall

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

1. Philipp Koehn
2. Chris Callison-Burch
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Alex Graves
6. Tomas Mikolov
7. Franz Joseph Och
8. Kyunghyun Cho
9. Ondrej Bojar
10. Ilya Sutskever

Who trusts Adam Lopez overall

1. Philipp Koehn
2. Ondrej Bojar
3. Christian Federmann
4. Mark Hopkins
5. Carolin (Haas) Lawrence
6. Mark Dras
7. Matt Post
8. Christian Buck
9. Lucia Specia
10. Barry Haddow

Papers from Adam Lopez's perspective

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

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

Their papers

• Dirt Cheap Web-Scale Parallel Text from the Common Crawl (2013) — 164 citations
• From Characters to Words to in Between: Do We Capture Morphology? (2017) — 103 citations
• Intrinsic Bias Metrics Do Not Correlate with Application Bias (2020) — 214 citations
• Pre-training on high-resource speech recognition improves low-resource speech-to-text translation (2018) — 216 citations
• Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2013) — 431 citations
• Putting Human Assessments of Machine Translation Systems in Order (2012) — 24 citations
• cdec: A Decoder, Alignment, and Learning Framework for Finite- State and Context-Free Translation Models (2010) — 254 citations
• Edinburgh Research Explorer A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages