Ignacio Iacobacci

Artificial Intelligence · 2015–2022

A researcher in the Science corpus: 5 papers; trusts 103 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 119 citations into it; #9,532 of 35,345 by trust here, #15,542 by citations
• Natural Language Processing — 107 citations into it; #2,668 of 5,688 by trust here, #4,539 by citations
• Representation & Self-Supervised Learning — 42 citations into it; #1,573 of 3,145 by trust here, #2,587 by citations
• Information Systems — 26 citations into it
• Computer Vision and Pattern Recognition — 25 citations into it; #11,651 of 21,575 by trust here, #16,367 by citations
• Large Language Models — 19 citations into it
• Evaluation & Benchmarks — 15 citations into it
• Model Architectures — 8 citations into it

Whom Ignacio Iacobacci trusts overall

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

1. Tomas Mikolov
2. Yoshua Bengio
3. Ronan Collobert
4. Geoffrey E. Hinton
5. Roberto Navigli
6. Richard Socher
7. Ilya Sutskever
8. George A. Miller
9. Jason Aaron Edward Weston
10. Diederik P. Kingma

Who trusts Ignacio Iacobacci overall

1. José Camacho-Collados
2. Mohammad Taher Pilehvar
3. Roberto Navigli
4. Alessandro Raganato
5. Massimiliano Mancini
6. Bianca Scarlini
7. Chris Biemann
8. Haim Dubossarsky
9. Mikhail Khodak
10. Matthew E. Peters

Papers from Ignacio Iacobacci's perspective

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

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

Their papers

• Embeddings for Word Sense Disambiguation: An Evaluation Study (2016) — 274 citations
• PanGu-Coder: Program Synthesis with Function-Level Language Modeling (2022) — 87 citations
• Conversation Graph: Data Augmentation, Training, and Evaluation for Non-Deterministic Dialogue Management (2020) — 20 citations
• Embedding Words and Senses Together via Joint Knowledge-Enhanced Training (2016) — 80 citations
• SensEmbed: Learning Sense Embeddings for Word and Relational Similarity (2015) — 296 citations