Julian Chow

Natural Language Processing · 2019

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 9 citations into it
• Artificial Intelligence — 8 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Julian Chow trusts overall

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

1. Ofir Pele
2. Michael Werman
3. Satanjeev Banerjee
4. Ondrej Bojar
5. Matt J. Kusner
6. Mert Kilickaya
7. Tomas Mikolov
8. Alon Lavie
9. Maja Popovic
10. Yvette Graham

Who trusts Julian Chow overall

1. Ananya B. Sai
2. Pierre Colombo
3. Tanay Dixit

Papers from Julian Chow's perspective

Ordered by how strongly the researchers Julian Chow trusts endorse each paper. Same corpus, a different order for every researcher.

1. Bleu: a Method for Automatic Evaluation of Machine Translation
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Efficient Estimation of Word Representations in Vector Space
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet classification with deep convolutional neural networks
8. Gradient-based learning applied to document recognition
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• WMDO: Fluency-based Word Mover’s Distance for Machine Translation Evaluation (2019) — 27 citations