Leonardo F. R. Ribeiro
Artificial Intelligence · with Gurevych · 2017–2022
A researcher in the Science corpus: 8 papers; trusts 223 researchers and is trusted by 27 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 245 citations into it; #7,372 of 35,345 by trust here, #5,495 by citations
- Natural Language Processing — 191 citations into it; #2,451 of 5,688 by trust here, #1,769 by citations
- Evaluation & Benchmarks — 78 citations into it
- Computer Vision and Pattern Recognition — 54 citations into it
- Graph Learning — 30 citations into it; #280 of 693 by trust here, #311 by citations
- Large Language Models — 25 citations into it
- Molecular Biology — 24 citations into it; #6,806 of 17,773 by trust here, #10,193 by citations
- Representation & Self-Supervised Learning — 24 citations into it
Whom Leonardo F. R. Ribeiro trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Yoshua Bengio
- Geoffrey E. Hinton
- Ilya Sutskever
- Jimmy Ba
- Alex Krizhevsky
- Tomas Mikolov
- Yann LeCun
- Jacob Devlin
- Alex Graves
Who trusts Leonardo F. R. Ribeiro overall
- Adyasha Maharana
- Benedek Rozemberczki
- Jordan Clive
- Pan Li
- Mohit Bansal
- Tanya Goyal
- Hamza Harkous
- Emma Manning
- Davide Bacciu
- Susheel Suresh
Papers from Leonardo F. R. Ribeiro's perspective
Ordered by how strongly the researchers Leonardo F. R. Ribeiro trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Ranking Generated Summaries by Correctness: An Interesting but Challenging Application for Natural Language Inference (2019) — 344 citations
- GEMv2: Multilingual NLG Benchmarking in a Single Line of Code (2022) — 43 citations
- Enhancing AMR-to-Text Generation with Dual Graph Representations (2019) — 66 citations
- struc2vec: Learning Node Representations from Structural Identity (2017) — 1,286 citations
- Investigating Pretrained Language Models for Graph-to-Text Generation (2020) — 233 citations
- Common Sense or World Knowledge? Investigating Adapter-Based Knowledge Injection into Pretrained Transformers (2020) — 93 citations
- Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs (2020) — 82 citations
- FactGraph: Evaluating Factuality in Summarization with Semantic Graph Representations (2022) — 73 citations