Cynthia Matuszek
Natural Language Processing · 2006–2020
A researcher in the Science corpus: 7 papers; trusts 155 researchers and is trusted by 73 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 70 citations into it; #1,281 of 5,688 by trust here, #1,170 by citations
- Artificial Intelligence — 67 citations into it; #4,920 of 35,345 by trust here, #4,353 by citations
- Computer Vision and Pattern Recognition — 56 citations into it; #4,071 of 21,575 by trust here, #3,538 by citations
- Reinforcement Learning — 21 citations into it; #1,807 of 2,242 by trust here, #1,501 by citations
- Multimodal Learning — 17 citations into it; #504 of 1,211 by trust here, #526 by citations
- Representation & Self-Supervised Learning — 8 citations into it
- LLM Agents & Tool Use — 5 citations into it; #91 of 124 by trust here, #110 by citations
Whom Cynthia Matuszek trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Raymond J. Mooney
- Luke S. Zettlemoyer
- Tomas Mikolov
- David L. Chen
- Tom Kwiatkowski
- Ilya Sutskever
- Yann LeCun
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
Who trusts Cynthia Matuszek overall
- Dipendra Kumar Misra
- Percy Liang
- Mohit Shridhar
- Mateusz Malinowski
- Siddharth Karamcheti
- Yonatan Bisk
- Yoav Artzi
- Jacob Andreas
- Moritz Tenorth
- Luke S. Zettlemoyer
Papers from Cynthia Matuszek's perspective
Ordered by how strongly the researchers Cynthia Matuszek trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- A Joint Model of Language and Perception for Grounded Attribute Learning (2012) — 323 citations
- Learning to Parse Natural Language Commands to a Robot Control System (2012) — 423 citations
- Robots That Use Language (2020) — 312 citations
- Learning from Unscripted Deictic Gesture and Language for Human-Robot Interactions (2014) — 158 citations
- Grounded Language Learning: Where Robotics and NLP Meet (2018) — 73 citations
- Unequal Representation and Gender Stereotypes in Image Search Results for Occupations (2015) — 573 citations
- An Introduction to the Syntax and Content of Cyc (2006) — 441 citations