Wojciech Stokowiec

Artificial Intelligence · 2019–2025

A researcher in the Science corpus: 6 papers; trusts 83 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 151 citations into it
• Natural Language Processing — 108 citations into it
• Computer Vision and Pattern Recognition — 59 citations into it
• Large Language Models — 39 citations into it
• Evaluation & Benchmarks — 24 citations into it
• Retrieval-Augmented Generation — 10 citations into it
• Optimization & Training — 6 citations into it
• Machine Translation — 5 citations into it

Whom Wojciech Stokowiec trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Rico Sennrich
5. Ilya Sutskever
6. Jimmy Ba
7. Alex Krizhevsky
8. Alec Radford
9. Yann LeCun
10. Alex Graves

Papers from Wojciech Stokowiec's perspective

Ordered by how strongly the researchers Wojciech Stokowiec trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Gradient-based learning applied to document recognition
10. ImageNet: A large-scale hierarchical image database

Their papers

• Internet-augmented language models through few-shot prompting for open-domain question answering (2022) — 177 citations
• Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context (2024) — 3,818 citations
• Gemma: Open Models Based on Gemini Research and Technology (2024) — 1,150 citations
• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
• Putting Machine Translation in Context with the Noisy Channel Model (2019) — 7 citations
• Better Document-Level Machine Translation with Bayes’ Rule (2019) — 48 citations