Louis Martin
Artificial Intelligence · 2019–2023
A researcher in the Science corpus: 7 papers; trusts 48 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 288 citations into it; #16,070 of 35,345 by trust here, #1,378 by citations
- Natural Language Processing — 177 citations into it; #4,239 of 5,688 by trust here, #2,385 by citations
- Evaluation & Benchmarks — 71 citations into it; #1,667 of 3,147 by trust here, #2,410 by citations
- Computer Vision and Pattern Recognition — 70 citations into it
- Efficiency & Compression — 33 citations into it
- Representation & Self-Supervised Learning — 23 citations into it
Whom Louis Martin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Tomas Mikolov
- Yoshua Bengio
- Ilya Sutskever
- Armand Joulin
- Alex Krizhevsky
- Noam Shazeer
- Jimmy Ba
- Yann LeCun
Who trusts Louis Martin overall
- Jordan Clive
- Thomas Scialom
- Pedro Ortiz Suarez
- Dat Quoc Nguyen
- Muhammad Abdul-Mageed
- Pieter Delobelle
- Kris Cao
- Tuhin Chakrabarty
- Julien Abadji
- Phillip Rust
Papers from Louis Martin's perspective
Ordered by how strongly the researchers Louis Martin trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- 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
- Llama 2: Open Foundation and Fine-Tuned Chat Models (2023) — 17,670 citations
- Efficient Large Scale Language Modeling with Mixtures of Experts (2021) — 248 citations
- CamemBERT: a Tasty French Language Model (2019) — 1,110 citations
- Code Llama: Open Foundation Models for Code (2023) — 3,394 citations
- ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations (2020) — 192 citations
- EASSE: Easier Automatic Sentence Simplification Evaluation (2019) — 149 citations
- MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases (2022) — 124 citations