Sylvain Lamprier
Artificial Intelligence · 2019–2023
A researcher in the Science corpus: 9 papers; trusts 342 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 279 citations into it; #10,941 of 35,345 by trust here, #7,858 by citations
- Natural Language Processing — 251 citations into it; #2,071 of 5,688 by trust here, #1,753 by citations
- Evaluation & Benchmarks — 105 citations into it
- Computer Vision and Pattern Recognition — 102 citations into it
- Large Language Models — 46 citations into it
- Reinforcement Learning — 29 citations into it
- Model Architectures — 27 citations into it
- Generative Models — 22 citations into it
Whom Sylvain Lamprier trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ronald J. Williams
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Diederik P. Kingma
- Chin-Yew Lin
- Alex Krizhevsky
- Tomas Mikolov
- Richard Socher
- Oriol Vinyals
Who trusts Sylvain Lamprier overall
- Thomas Scialom
- Rowan Zellers
- Sebastian Gehrmann
- Philippe Laban
- Alex Wang
- Shuyang Cao
- Elizabeth Clark
- Or Honovich
- Esin Durmus
- Alexander R. Fabbri
Papers from Sylvain Lamprier's perspective
Ordered by how strongly the researchers Sylvain Lamprier trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- 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)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- 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
- MLSUM: The Multilingual Summarization Corpus (2020) — 213 citations
- Answers Unite! Unsupervised Metrics for Reinforced Summarization Models (2019) — 162 citations
- ColdGANs: Taming Language GANs with Cautious Sampling Strategies (2020) — 18 citations
- QuestEval: Summarization Asks for Fact-based Evaluation (2021) — 371 citations
- Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning (2023) — 272 citations
- Learning Dynamic Author Representations with Temporal Language Models (2019) — 10 citations
- Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation (2021) — 38 citations
- SAFEval: Summarization Asks for Fact-based Evaluation (2021) — 5 citations
- Discriminative Adversarial Search for Abstractive Summarization (2020) — 37 citations