Dima Rekesh

Artificial Intelligence · 2024

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 38 citations into it
• Model Architectures — 18 citations into it
• Natural Language Processing — 5 citations into it

Whom Dima Rekesh trusts

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

1. Vincent Ng (in Natural Language Processing)
2. John J. Hopfield (in Model Architectures)
3. Yoshua Bengio (in Artificial Intelligence)
4. Ilya Sutskever (in Artificial Intelligence)

Papers from Dima Rekesh's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Generating Long Sequences with Sparse Transformers
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Know What You Don’t Know: Unanswerable Questions for SQuAD
10. ImageNet: A large-scale hierarchical image database

Their papers

• RULER: What's the Real Context Size of Your Long-Context Language Models? (2024) — 1,085 citations