Xilun Chen

Artificial Intelligence · 2016–2022

A researcher in the Science corpus: 9 papers; trusts 297 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 301 citations into it; #10,939 of 35,345 by trust here, #5,880 by citations
• Natural Language Processing — 201 citations into it; #4,163 of 5,688 by trust here, #3,154 by citations
• Computer Vision and Pattern Recognition — 121 citations into it
• Information Retrieval & Search — 101 citations into it
• Evaluation & Benchmarks — 78 citations into it
• Representation & Self-Supervised Learning — 48 citations into it; #2,355 of 3,145 by trust here, #1,754 by citations
• Large Language Models — 37 citations into it
• Generative Models — 12 citations into it

Whom Xilun Chen trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Tomas Mikolov
4. Diederik P. Kingma
5. Ilya Sutskever
6. Alex Krizhevsky
7. Richard Socher
8. Individualized Treat
9. Christopher D. Manning
10. Yoon Kim

Who trusts Xilun Chen overall

1. Antonios Anastasopoulos
2. Nina Poerner
3. Eyal Ben-David
4. Graham Neubig
5. Claire Cardie
6. Chia-Hsuan Lee
7. Percy Liang
8. Hinrich Schütze
9. Wayne Xin Zhao
10. Qizhe Xie

Papers from Xilun Chen's perspective

Ordered by how strongly the researchers Xilun Chen 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
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

• Muppet: Massive Multi-task Representations with Pre-Finetuning (2021) — 301 citations
• Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification (2016) — 330 citations
• Task-aware Retrieval with Instructions (2022) — 139 citations
• Domain-matched Pre-training Tasks for Dense Retrieval (2021) — 72 citations
• UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering (2020) — 106 citations
• Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One? (2021) — 87 citations
• Multinomial Adversarial Networks for Multi-Domain Text Classification (2018) — 139 citations
• CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training (2021) — 16 citations
• Unsupervised Multilingual Word Embeddings (2018) — 141 citations