Jelena Mitrović

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 27 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it; #34,672 of 35,345 by trust here, #25,040 by citations
• Natural Language Processing — 53 citations into it; #5,432 of 5,688 by trust here, #4,032 by citations
• Safety, Robustness & Interpretability — 29 citations into it; #2,197 of 2,251 by trust here, #1,857 by citations
• Communication — 17 citations into it
• Information Systems — 14 citations into it
• AI Ethics, Fairness & Society — 9 citations into it
• Evaluation & Benchmarks — 8 citations into it
• Social Psychology — 7 citations into it

Whom Jelena Mitrović trusts overall

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

1. Marcos Zampieri
2. Diederik P. Kingma
3. Kaiming He
4. Michael Wiegand
5. Anna Schmidt
6. Shervin Malmasi
7. Kyunghyun Cho
8. Jimmy Ba
9. Thomas Davidson
10. Yoshua Bengio

Who trusts Jelena Mitrović overall

1. Jiawen Deng

Papers from Jelena Mitrović's perspective

Ordered by how strongly the researchers Jelena Mitrović 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Long Short-Term Memory
4. ImageNet classification with deep convolutional neural networks
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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• HateBERT: Retraining BERT for Abusive Language Detection in English (2020) — 503 citations
• I Feel Offended, Don’t Be Abusive! Implicit/Explicit Messages in Offensive and Abusive Language (2020) — 180 citations
• nlpUP at SemEval-2019 Task 6: A Deep Neural Language Model for Offensive Language Detection (2019) — 25 citations