Iulia Turc
Artificial Intelligence · 2019–2022
A researcher in the Science corpus: 7 papers; trusts 195 researchers and is trusted by 16 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 218 citations into it; #16,546 of 35,345 by trust here, #7,797 by citations
- Natural Language Processing — 153 citations into it
- Computer Vision and Pattern Recognition — 108 citations into it
- Evaluation & Benchmarks — 54 citations into it
- Large Language Models — 51 citations into it
- Efficiency & Compression — 33 citations into it
- Model Architectures — 29 citations into it
- Representation & Self-Supervised Learning — 20 citations into it; #1,273 of 3,145 by trust here, #1,127 by citations
Whom Iulia Turc trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Ilya Sutskever
- Richard Socher
- Yoshua Bengio
- Tomas Mikolov
- Diederik P. Kingma
- Alex Krizhevsky
- Alex Graves
- Christopher D. Manning
- Yann LeCun
Who trusts Iulia Turc overall
- Angela Fan
- Victor Sanh
- Jianping Gou
- Shaojun Zhou
- Hadi Pouransari
- Wenhui Wang
- Subhabrata Mukherjee
- Anna Rogers
- Canwen Xu
- Jimmy J. Lin
Papers from Iulia Turc's perspective
Ordered by how strongly the researchers Iulia Turc trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Measuring Attribution in Natural Language Generation Models (2021) — 277 citations
- Canine: Pre-training an Efficient Tokenization-Free Encoder for Language Representation (2021) — 314 citations
- Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding (2022) — 473 citations
- Well-Read Students Learn Better: The Impact of Student Initialization on Knowledge Distillation (2019) — 250 citations
- The MultiBERTs: BERT Reproductions for Robustness Analysis (2021) — 110 citations
- High Performance Natural Language Processing (2020) — 6 citations
- Well-Read Students Learn Better: On the Importance of Pre-training Compact Models (2019) — 775 citations