Max Kaufmann

Artificial Intelligence · 2023

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 22 citations into it
• Large Language Models — 12 citations into it
• Natural Language Processing — 7 citations into it

Whom Max Kaufmann trusts overall

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

1. Sosuke Kobayashi
2. Michael R Douglas

Papers from Max Kaufmann's perspective

Ordered by how strongly the researchers Max Kaufmann 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. Language Models are Few-Shot Learners (Neural Information Processing Systems)
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Long Short-Term Memory
6. ImageNet classification with deep convolutional neural networks
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. ImageNet: A large-scale hierarchical image database

Their papers

• The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A" (2023) — 511 citations