Rahul Jha

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it
• Natural Language Processing — 54 citations into it
• Evaluation & Benchmarks — 29 citations into it

Whom Rahul Jha trusts overall

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

1. Chin-Yew Lin
2. George A. Miller
3. Noam Shazeer
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Diederik P. Kingma
7. Ilya Sutskever
8. Oriol Vinyals
9. Kyunghyun Cho
10. Alex Krizhevsky

Papers from Rahul Jha's perspective

Ordered by how strongly the researchers Rahul Jha 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet classification with deep convolutional neural networks
6. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Gradient-based learning applied to document recognition
10. ImageNet: A large-scale hierarchical image database

Their papers

• QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization (2021) — 488 citations
• GO FIGURE: A Meta Evaluation of Factuality in Summarization (2020) — 107 citations