Ricardo Usbeck
Natural Language Processing · 2014–2022
A researcher in the Science corpus: 4 papers; trusts 42 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 53 citations into it; #3,311 of 5,688 by trust here, #4,793 by citations
- Artificial Intelligence — 51 citations into it; #19,293 of 35,345 by trust here, #26,682 by citations
- Evaluation & Benchmarks — 19 citations into it; #1,775 of 3,147 by trust here, #2,704 by citations
- Information Systems — 10 citations into it
Whom Ricardo Usbeck trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Silviu Cucerzan
- Johannes Hoffart
- Roberto Navigli
- Oriol Vinyals
- Satanjeev Banerjee
- Benjamin Snyder
- Yoshua Bengio
- Nadine Steinmetz
- Pablo N. Mendes
- Alan Ritter
Who trusts Ricardo Usbeck overall
- Nicola De Cao
- Armen Aghajanyan
- Nikolaos Kolitsas
- Gautier Izacard
- Johannes M. van Hulst
- Michael Röder
Papers from Ricardo Usbeck's perspective
Ordered by how strongly the researchers Ricardo Usbeck trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
- 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
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- GERBIL - Benchmarking Named Entity Recognition and Linking consistently (2017) — 95 citations
- N³ - A Collection of Datasets for Named Entity Recognition and Disambiguation in the NLP Interchange Format (2014) — 94 citations
- RoMe: A Robust Metric for Evaluating Natural Language Generation (2022) — 16 citations
- Treating Dialogue Quality Evaluation as an Anomaly Detection Problem (2020) — 7 citations