Marco Marelli
Natural Language Processing · 2011–2020
A researcher in the Science corpus: 7 papers; trusts 21 researchers and is trusted by 54 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 70 citations into it; #1,352 of 5,688 by trust here, #1,000 by citations
- Artificial Intelligence — 57 citations into it; #5,048 of 35,345 by trust here, #4,119 by citations
- Developmental and Educational Psychology — 36 citations into it; #7,034 of 8,223 by trust here, #4,447 by citations
- Cognitive Neuroscience — 32 citations into it; #9,313 of 10,852 by trust here, #6,723 by citations
- Representation & Self-Supervised Learning — 23 citations into it; #2,085 of 3,145 by trust here, #2,587 by citations
- Language and Linguistics — 16 citations into it
- Experimental and Cognitive Psychology — 12 citations into it; #8,263 of 9,731 by trust here, #5,729 by citations
- Computer Vision and Pattern Recognition — 8 citations into it
Whom Marco Marelli trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jeff Mitchell
- Edward Grefenstette
- Marco Baroni
- Mirella Lapata
- Eneko Agirre
- Mehrnoosh Sadrzadeh
- R. Harald Baayen
- Richard Socher
- Christopher D. Manning
- Bill MacCartney
Who trusts Marco Marelli overall
- Samuel R. Bowman
- Lasha Abzianidze
- Alexis Conneau
- Bowen Zhang
- Douwe Kiela
- Christopher D. Manning
- Kawin Ethayarajh
- Mohit Bansal
- Shuai Tang
- Hai Hu
Papers from Marco Marelli's perspective
Ordered by how strongly the researchers Marco Marelli trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- A SICK cure for the evaluation of compositional distributional semantic models (2014) — 963 citations
- SemEval-2014 Task 1: Evaluation of Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment (2014) — 450 citations
- SICK through the SemEval glasses. Lesson learned from the evaluation of compositional distributional semantic models on full sentences through semantic relatedness and textual entailment (2016) — 62 citations
- Mechanisms for handling nested dependencies in neural-network language models and humans. (2020) — 75 citations
- Compositional-ly Derived Representations of Morphologically Complex Words in Distributional Semantics (2013) — 115 citations
- Frequency Effects in the Processing of Italian Nominal Compounds: Modulation of Headedness and Semantic Transparency (2012) — 129 citations
- An amorphous model for morphological processing in visual comprehension based on naive discriminative learning. (2011) — 524 citations