Marine Carpuat
Artificial Intelligence · 2007–2024
A researcher in the Science corpus: 17 papers; trusts 648 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 404 citations into it; #16,316 of 35,345 by trust here, #12,387 by citations
- Natural Language Processing — 344 citations into it; #3,192 of 5,688 by trust here, #3,638 by citations
- Computer Vision and Pattern Recognition — 137 citations into it; #11,654 of 21,575 by trust here, #11,286 by citations
- Evaluation & Benchmarks — 109 citations into it
- Large Language Models — 58 citations into it
- Optimization & Training — 36 citations into it
- Model Architectures — 35 citations into it
- Representation & Self-Supervised Learning — 33 citations into it
Whom Marine Carpuat trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Rico Sennrich
- Philipp Koehn
- Yoshua Bengio
- Geoffrey E. Hinton
- Franz Joseph Och
- Jimmy Ba
- Ilya Sutskever
- Alex Krizhevsky
- Kyunghyun Cho
Who trusts Marine Carpuat overall
- Yonatan Belinkov
- Ziwei Ji
- Weijia Xu
- José Camacho-Collados
- Ahmed Elgohary
- Nayeon Lee
- Roberto Navigli
- Zhi Zhong
- Isaac Caswell
- Mohammad Taher Pilehvar
Papers from Marine Carpuat's perspective
Ordered by how strongly the researchers Marine Carpuat trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- 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)
- 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)
- ImageNet: A large-scale hierarchical image database
Their papers
- Bi-Directional Neural Machine Translation with Synthetic Parallel Data (2018) — 60 citations
- Curriculum Learning for Domain Adaptation in Neural Machine Translation (2019) — 131 citations
- Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer (2021) — 39 citations
- An Empirical Exploration of Curriculum Learning for Neural Machine Translation (2018) — 125 citations
- The Prompt Report: A Systematic Survey of Prompting Techniques (2024) — 309 citations
- BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022) — 2,975 citations
- A Review of Human Evaluation for Style Transfer (2021) — 32 citations
- Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation (2021) — 15 citations
- Rule-based Morphological Inflection Improves Neural Terminology Translation (2021) — 6 citations
- EDITOR: An Edit-Based Transformer with Repositioning for Neural Machine Translation with Soft Lexical Constraints (2020) — 52 citations
- Identifying Fluently Inadequate Output in Neural and Statistical Machine Translation (2019) — 34 citations
- Differentiable Sampling with Flexible Reference Word Order for Neural Machine Translation (2019) — 10 citations
- The University of Maryland’s Kazakh-English Neural Machine Translation System at WMT19 (2019) — 15 citations
- Detecting Asymmetric Semantic Relations in Context: A Case-Study on Hypernymy Detection (2017) — 10 citations
- Learning Monolingual Compositional Representations via Bilingual Supervision (2016)
- Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017) (2015) — 47 citations
- Improving Statistical Machine Translation Using Word Sense Disambiguation (2007) — 410 citations