Antonios Anastasopoulos

Artificial Intelligence · 2016–2022

A researcher in the Science corpus: 16 papers; trusts 657 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 516 citations into it; #8,358 of 35,345 by trust here, #4,063 by citations
• Natural Language Processing — 422 citations into it; #2,666 of 5,688 by trust here, #2,263 by citations
• Computer Vision and Pattern Recognition — 139 citations into it; #8,939 of 21,575 by trust here, #7,852 by citations
• Safety, Robustness & Interpretability — 94 citations into it
• Evaluation & Benchmarks — 93 citations into it; #1,420 of 3,147 by trust here, #2,671 by citations
• Large Language Models — 69 citations into it
• Representation & Self-Supervised Learning — 48 citations into it
• Model Architectures — 46 citations into it

Whom Antonios Anastasopoulos trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Ilya Sutskever
5. Alex Krizhevsky
6. Dzmitry Bahdanau
7. Alex Graves
8. Kyunghyun Cho
9. Philipp Koehn
10. Tomas Mikolov

Who trusts Antonios Anastasopoulos overall

1. Changhan Wang
2. Mattia Antonino Di Gangi
3. Michelle Guo
4. Timo Schick
5. Xian Li
6. Hirofumi Inaguma
7. Jiajun Zhang
8. Yun Tang
9. Juan Pino
10. Matthias Sperber

Papers from Antonios Anastasopoulos's perspective

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

Their papers

• DyNet: The Dynamic Neural Network Toolkit (2017) — 391 citations
• X-FACTR: Multilingual Factual Knowledge Retrieval from Pretrained Language Models (2020) — 165 citations
• Tied Multitask Learning for Neural Speech Translation (2018) — 180 citations
• Should All Cross-Lingual Embeddings Speak English? (2019) — 34 citations
• Choosing Transfer Languages for Cross-Lingual Learning (2019) — 265 citations
• Generalized Data Augmentation for Low-Resource Translation (2019) — 128 citations
• Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks (2019) — 130 citations
• Freezing Subnetworks to Analyze Domain Adaptation in Neural Machine Translation (2018) — 56 citations
• An Attentional Model for Speech Translation Without Transcription (2016) — 156 citations
• Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey (2022) — 119 citations
• Evaluating the Morphosyntactic Well-formedness of Generated Texts (2021) — 11 citations
• Machine Translation into Low-resource Language Varieties (2021) — 34 citations
• It’s not a Non-Issue: Negation as a Source of Error in Machine Translation (2020) — 32 citations
• Universal Phone Recognition with a Multilingual Allophone System (2020) — 172 citations
• SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection (2020) — 90 citations
• Towards Robust Toxic Content Classification (2019) — 41 citations