Alexandra Chronopoulou

Artificial Intelligence · with Li · 2019–2024

A researcher in the Science corpus: 3 papers; trusts 94 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 46 citations into it; #13,411 of 35,345 by trust here, #18,186 by citations
• Natural Language Processing — 38 citations into it; #2,514 of 5,688 by trust here, #3,638 by citations
• Computer Vision and Pattern Recognition — 20 citations into it; #15,843 of 21,575 by trust here, #19,766 by citations
• Model Architectures — 10 citations into it
• Representation & Self-Supervised Learning — 10 citations into it
• Evaluation & Benchmarks — 7 citations into it

Whom Alexandra Chronopoulou trusts overall

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

1. Yoshua Bengio
2. Diederik P. Kingma
3. Rico Sennrich
4. Geoffrey E. Hinton
5. Ilya Sutskever
6. Sepp Hochreiter
7. Dzmitry Bahdanau
8. Tomas Mikolov
9. Alex Krizhevsky
10. Jimmy Ba

Who trusts Alexandra Chronopoulou overall

1. Timo Schick
2. Sachin Kumar
3. Sebastian Gehrmann
4. Hinrich Schütze
5. Constantinos F. Karouzos
6. Guokun Lai
7. Xipeng Qiu
8. Zachary M. Ziegler
9. Yulong Chen
10. Suchin Gururangan

Papers from Alexandra Chronopoulou's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
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

• An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models (2019) — 143 citations
• Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context (2024) — 3,818 citations
• Reusing a Pretrained Language Model on Languages with Limited Corpora for Unsupervised NMT (2020) — 36 citations