Xi Ye

Artificial Intelligence · 2021–2024

A researcher in the Science corpus: 4 papers; trusts 337 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 141 citations into it; #35,124 of 35,345 by trust here, #17,110 by citations
• Natural Language Processing — 77 citations into it
• Computer Vision and Pattern Recognition — 49 citations into it
• Large Language Models — 41 citations into it
• Prompting & Reasoning — 36 citations into it; #359 of 359 by trust here, #288 by citations
• Evaluation & Benchmarks — 17 citations into it
• Safety, Robustness & Interpretability — 14 citations into it
• Information Systems — 11 citations into it

Whom Xi Ye trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. J. Platt
5. Jason Aaron Edward Weston
6. Alex Krizhevsky
7. Ilya Sutskever
8. Yann LeCun
9. Kaiming He
10. Nazneen Rajani

Who trusts Xi Ye overall

1. Xuezhi Wang
2. Omar Shaikh
3. Jacob Eisenstein
4. Jason Wei
5. Linhao Luo
6. Hongxin Zhang
7. D. Andor
8. Jie Huang
9. Dale Schuurmans
10. Tianbao Xie

Papers from Xi Ye's perspective

Ordered by how strongly the researchers Xi Ye 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. Attention is All you Need (Neural Information Processing Systems)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. ImageNet: A large-scale hierarchical image database
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• The Unreliability of Explanations in Few-Shot In-Context Learning (2022) — 37 citations
• RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering (2021) — 212 citations
• The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning (2022) — 259 citations
• To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning (2024) — 338 citations