Vasin Punyakanok

Artificial Intelligence · 2001–2008

A researcher in the Science corpus: 4 papers; trusts 23 researchers and is trusted by 57 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it; #3,482 of 35,345 by trust here, #8,810 by citations
• Natural Language Processing — 20 citations into it; #1,399 of 5,688 by trust here, #2,567 by citations
• Information Extraction — 12 citations into it; #133 of 407 by trust here, #157 by citations
• Evaluation & Benchmarks — 8 citations into it
• Molecular Biology — 5 citations into it

Whom Vasin Punyakanok trusts overall

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

1. Michael Collins
2. Charles M. Bishop
3. Martha Palmer
4. Xavier Carreras
5. D. Bikel
6. Yoav Freund
7. Dan Roth
8. Daniel Gildea
9. Nianwen Xue
10. Mitchell P. Marcus

Who trusts Vasin Punyakanok overall

1. Dan Roth
2. Subhro Roy
3. Andrew McCallum
4. Wen-tau Yih
5. Daniel Khashabi
6. Ming-Wei Chang
7. Lev-Arie Ratinov
8. Vivek Srikumar
9. Bishan Yang
10. Xin Li

Papers from Vasin Punyakanok's perspective

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

1. Long Short-Term Memory
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Attention is All you Need (Neural Information Processing Systems)
6. Building a Large Annotated Corpus of English: The Penn Treebank
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• The Importance of Syntactic Parsing and Inference in Semantic Role Labeling (2008) — 451 citations
• Generalized Inference with Multiple Semantic Role Labeling Systems (2005) — 156 citations
• The Use of Classifiers in Sequential Inference (2001) — 219 citations
• The Necessity of Syntactic Parsing for Semantic Role Labeling (2005) — 135 citations