Jason Riesa
Artificial Intelligence · 2016–2023
A researcher in the Science corpus: 11 papers; trusts 108 researchers and is trusted by 16 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 358 citations into it; #12,039 of 35,345 by trust here, #748 by citations
- Natural Language Processing — 227 citations into it; #3,332 of 5,688 by trust here, #193 by citations
- Speech & Audio — 127 citations into it
- Computer Vision and Pattern Recognition — 99 citations into it; #19,638 of 21,575 by trust here, #675 by citations
- Evaluation & Benchmarks — 88 citations into it
- Signal Processing — 79 citations into it
- Large Language Models — 48 citations into it
- Model Architectures — 35 citations into it
Whom Jason Riesa trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- L. Eon Bottou
- Yoshua Bengio
- Alex Graves
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Yann LeCun
- Tomas Mikolov
- Oriol Vinyals
Who trusts Jason Riesa overall
Papers from Jason Riesa's perspective
Ordered by how strongly the researchers Jason Riesa 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
Their papers
- Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation (2016) — 7,325 citations
- Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation (2019) — 76 citations
- Building Machine Translation Systems for the Next Thousand Languages (2022) — 120 citations
- mSLAM: Massively multilingual joint pre-training for speech and text (2022) — 133 citations
- FRMT: A Benchmark for Few-Shot Region-Aware Machine Translation (2022) — 27 citations
- FLEURS: FEW-Shot Learning Evaluation of Universal Representations of Speech (2022) — 651 citations
- SLAM: A Unified Encoder for Speech and Language Modeling via Speech-Text Joint Pre-Training (2021) — 102 citations
- Small and Practical BERT Models for Sequence Labeling (2019) — 128 citations
- Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages (2023) — 396 citations
- A Fast, Compact, Accurate Model for Language Identification of Codemixed Text (2018) — 36 citations
- XTREME-S: Evaluating Cross-lingual Speech Representations (2022) — 27 citations