Xinran Zhao
Artificial Intelligence · 2020–2023
A researcher in the Science corpus: 4 papers; trusts 21 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 52 citations into it; #18,769 of 35,345 by trust here, #18,586 by citations
- Natural Language Processing — 46 citations into it; #3,236 of 5,688 by trust here, #3,687 by citations
- Evaluation & Benchmarks — 12 citations into it; #1,726 of 3,147 by trust here, #581 by citations
Whom Xinran Zhao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Sepp Hochreiter
- M. McHugh
- Marco Tulio Ribeiro
- Jeffrey Pennington
- Geoffrey E. Hinton
- J. Urgen Schmidhuber
- Yoshua Bengio
- Richard Socher
- Altaf Rahman
- Diederik P. Kingma
Who trusts Xinran Zhao overall
Papers from Xinran Zhao's perspective
Ordered by how strongly the researchers Xinran Zhao trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- GloVe: Global Vectors for Word Representation
- Gradient-based learning applied to document recognition
- Language Models are Unsupervised Multitask Learners
- ImageNet: A large-scale hierarchical image database
Their papers
- WinoWhy: A Deep Diagnosis of Essential Commonsense Knowledge for Answering Winograd Schema Challenge (2020) — 60 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2023) — 266 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations
- Probing Toxic Content in Large Pre-Trained Language Models (2021) — 148 citations