Qiantong Xu

Artificial Intelligence · 2018–2022

A researcher in the Science corpus: 17 papers; trusts 646 researchers and is trusted by 62 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 472 citations into it; #4,020 of 35,345 by trust here, #2,271 by citations
• Natural Language Processing — 225 citations into it; #1,085 of 5,688 by trust here, #795 by citations
• Speech & Audio — 221 citations into it; #186 of 1,076 by trust here, #89 by citations
• Signal Processing — 201 citations into it; #1,450 of 7,572 by trust here, #586 by citations
• Computer Vision and Pattern Recognition — 194 citations into it; #20,545 of 21,575 by trust here, #7,176 by citations
• Representation & Self-Supervised Learning — 107 citations into it; #3,134 of 3,145 by trust here, #1,103 by citations
• Model Architectures — 95 citations into it
• Evaluation & Benchmarks — 54 citations into it; #1,489 of 3,147 by trust here, #1,233 by citations

Whom Qiantong Xu trusts overall

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

1. Alex Graves
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Ilya Sutskever
6. Alex Krizhevsky
7. Kaiming He
8. Ronan Collobert
9. Yann LeCun
10. Ashish Vaswani

Who trusts Qiantong Xu overall

1. Wei-Ning Hsu
2. Alexei Baevski
3. Tatiana Likhomanenko
4. Vineel Pratap
5. Abdel-rahman Mohamed
6. Changhan Wang
7. Gabriel Synnaeve
8. Jacob Kahn
9. Yu Zhang
10. Alexis Conneau

Papers from Qiantong Xu's perspective

Ordered by how strongly the researchers Qiantong Xu 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language (2022) — 1,194 citations
• Libri-Light: A Benchmark for ASR with Limited or No Supervision (2019) — 820 citations
• An empirical study on evaluation metrics of generative adversarial networks (2018) — 306 citations
• End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures (2019) — 264 citations
• Self-Training and Pre-Training are Complementary for Speech Recognition (2020) — 180 citations
• MLS: A Large-Scale Multilingual Dataset for Speech Research (2020) — 803 citations
• XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale (2021) — 1,102 citations
• CAPE: Encoding Relative Positions with Continuous Augmented Positional Embeddings (2021) — 73 citations
• Rethinking Evaluation in ASR: Are Our Models Robust Enough? (2020) — 111 citations
• Robust wav2vec 2.0: Analyzing Domain Shift in Self-Supervised Pre-Training (2021) — 279 citations
• Fully Convolutional Speech Recognition (2018) — 98 citations
• Scaling Up Online Speech Recognition Using ConvNets (2020) — 48 citations
• Self-Training for End-to-End Speech Translation (2020) — 69 citations
• Iterative Pseudo-Labeling for Speech Recognition (2020) — 156 citations
• slimIPL: Language-Model-Free Iterative Pseudo-Labeling (2020) — 73 citations
• Sequence-to-Sequence Speech Recognition with Time-Depth Separable Convolutions (2019) — 109 citations
• Wav2Letter++: A Fast Open-source Speech Recognition System (2018) — 168 citations