Marc Marone
Artificial Intelligence · 2019–2025
A researcher in the Science corpus: 7 papers; trusts 86 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 173 citations into it
- Natural Language Processing — 86 citations into it
- Large Language Models — 85 citations into it
- Evaluation & Benchmarks — 54 citations into it
- Information Systems — 33 citations into it
- Safety, Robustness & Interpretability — 25 citations into it
- Information Retrieval & Search — 11 citations into it
- Algorithms & Complexity — 6 citations into it
Whom Marc Marone trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Andrei Z. Broder
- Geoffrey E. Hinton
- Yoshua Bengio
- Alec Radford
- Ilya Sutskever
- Diederik P. Kingma
- Alex Krizhevsky
- Benjamin Van Durme
- Yann LeCun
- Kaiming He
Who trusts Marc Marone overall
Papers from Marc Marone's perspective
Ordered by how strongly the researchers Marc Marone trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- 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
- StarCoder: may the source be with you! (2023) — 1,263 citations
- Selecting, Planning, and Rewriting: A Modular Approach for Data-to-Document Generation and Translation (2019) — 8 citations
- “According to . . . ”: Prompting Language Models Improves Quoting from Pre-Training Data (2023) — 63 citations
- Seq vs Seq: An Open Suite of Paired Encoders and Decoders (2025)
- mmBERT: A Modern Multilingual Encoder with Annealed Language Learning (2025)
- StarCoder 2 and The Stack v2: The Next Generation (2024) — 698 citations
- Data Portraits: Recording Foundation Model Training Data (2023) — 43 citations