Ji Ma
Artificial Intelligence · with Hall · 2017–2022
A researcher in the Science corpus: 6 papers; trusts 110 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 168 citations into it; #29,145 of 35,345 by trust here, #6,517 by citations
- Natural Language Processing — 110 citations into it
- Information Retrieval & Search — 70 citations into it; #1,001 of 1,022 by trust here, #340 by citations
- Computer Vision and Pattern Recognition — 67 citations into it
- Large Language Models — 37 citations into it
- Evaluation & Benchmarks — 33 citations into it
- Prompting & Reasoning — 9 citations into it
- General Social Sciences — 7 citations into it
Whom Ji Ma trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Jacob Devlin
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Yann LeCun
- Ashish Vaswani
- Kenton C. T. Lee
- Kaiming He
Who trusts Ji Ma overall
- Jimmy J. Lin
- Bhaskar Mitra
- Hong-Liu Cao
- Lee Xiong
- Sebastian Hofstätter
- Liang Wang
- Wayne Xin Zhao
- Rodrigo Nogueira
- Andreas Ruckl'e
- John X. Morris
Papers from Ji Ma's perspective
Ordered by how strongly the researchers Ji Ma 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
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Large Dual Encoders Are Generalizable Retrievers (2021) — 644 citations
- Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models (2021) — 830 citations
- Natural Language Processing with Small Feed-Forward Networks (2017) — 39 citations
- QURIOUS: Question Generation Pretraining for Text Generation (2020) — 16 citations
- Promptagator: Few-shot Dense Retrieval From 8 Examples (2022) — 350 citations
- Zero-shot Neural Retrieval via Domain-targeted Synthetic Query Generation (2020) — 32 citations