Marco Polignano

Artificial Intelligence · 2019–2026

A researcher in the Science corpus: 3 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it
• Natural Language Processing — 24 citations into it
• Computer Vision and Pattern Recognition — 13 citations into it
• Representation & Self-Supervised Learning — 11 citations into it
• Large Language Models — 9 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Information Retrieval & Search — 5 citations into it

Whom Marco Polignano trusts overall

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

1. Alec Radford
2. Tomas Mikolov
3. Ilya Sutskever
4. Geoffrey E. Hinton
5. Ashish Vaswani
6. Yoshua Bengio
7. Diederik P. Kingma
8. Alex Krizhevsky
9. Yukun Zhu
10. Kaiming He

Who trusts Marco Polignano overall

1. Komal Florio
2. Wietse de Vries
3. Abhik Bhattacharjee
4. Valerio Basile

Papers from Marco Polignano's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Time of Your Hate: The Challenge of Time in Hate Speech Detection on Social Media (2020) — 104 citations
• Balancing hierarchical representation and quantization: A performance trade-off in text embeddings (2026)
• AlBERTo: Italian BERT Language Understanding Model for NLP Challenging Tasks Based on Tweets (2019) — 235 citations