Colin Phillips

Cognitive Neuroscience · Linguistic Inquiry · 2003–2018

A researcher in the Science corpus: 13 papers; trusts 77 researchers and is trusted by 37 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 112 citations into it; #1,003 of 10,852 by trust here, #1,882 by citations
• Developmental and Educational Psychology — 80 citations into it; #2,965 of 8,223 by trust here, #1,839 by citations
• Artificial Intelligence — 53 citations into it; #6,850 of 35,345 by trust here, #10,319 by citations
• Experimental and Cognitive Psychology — 40 citations into it
• Natural Language Processing — 37 citations into it; #2,853 of 5,688 by trust here, #3,754 by citations
• Language and Linguistics — 35 citations into it; #364 of 3,093 by trust here, #417 by citations
• Linguistics — 16 citations into it
• Representation & Self-Supervised Learning — 15 citations into it; #1,763 of 3,145 by trust here, #2,217 by citations

Whom Colin Phillips trusts overall

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

1. Mark Steedman
2. Noam Chomsky
3. Peter Hagoort
4. Steven Pinker
5. Angela D. Friederici
6. Brian McElree
7. Herbert H. Clark
8. R. Harald Baayen
9. Geoffrey E. Hinton
10. A. Prince

Who trusts Colin Phillips overall

1. Jon Sprouse
2. Benjamin Bruening
3. Andrew Radford
4. Alex Warstadt
5. Fernanda Ferreira
6. Sandra Chung
7. De Vries
8. Nina Kazanina
9. Morten H. Christiansen
10. H. Sigurðsson

Papers from Colin Phillips's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Assessing Composition in Sentence Vector Representations (2018) — 84 citations
• Agreement attraction in Spanish comprehension (2015) — 140 citations
• Contrasting intrusion profiles for agreement and anaphora: Experimental and modeling evidence (2013) — 292 citations
• A test of the relation between working-memory capacity and syntactic island effects (2012) — 251 citations
• The linguistic processes underlying the P600 (2010) — 284 citations
• Syntax at Age Two: Cross-Linguistic Differences (2010) — 94 citations
• Equal Treatment for All Antecedents: How Children Succeed with Principle B (2009) — 148 citations
• Agreement Attraction in Comprehension: Representations and Processes. (2009) — 491 citations
• A cortical network for semantics: (de)constructing the N400 (2008) — 1,626 citations
• The effect of syntactic constraints on the processing of backwards anaphora (2007) — 165 citations
• The Real-Time Status of Island Phenomena (2007) — 237 citations
• Processing filler-gap dependencies in a head-final language (2004) — 229 citations
• Linear Order and Constituency (2003) — 316 citations