Disha Shrivastava

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 20 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it; #27,880 of 35,345 by trust here, #25,809 by citations
• Large Language Models — 15 citations into it; #558 of 799 by trust here, #715 by citations
• Information Systems — 13 citations into it; #6,473 of 8,771 by trust here, #5,942 by citations
• Prompting & Reasoning — 12 citations into it
• Natural Language Processing — 10 citations into it

Whom Disha Shrivastava trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Jimmy Ba
4. Yoshua Bengio
5. Vincent J. Hellendoorn
6. Alex Krizhevsky
7. Kaiming He
8. Ilya Sutskever
9. Ashish Vaswani
10. Xiang Lisa Li

Who trusts Disha Shrivastava overall

1. Tianyang Liu
2. Naman Jain
3. Fengji Zhang
4. Canwen Xu
5. Banghao Chen

Papers from Disha Shrivastava's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Repository-Level Prompt Generation for Large Language Models of Code (2022) — 193 citations