Dheeru Dua
Artificial Intelligence · 2017–2025
A researcher in the Science corpus: 9 papers; trusts 289 researchers and is trusted by 53 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 270 citations into it; #4,002 of 35,345 by trust here, #2,327 by citations
- Natural Language Processing — 214 citations into it; #1,223 of 5,688 by trust here, #845 by citations
- Computer Vision and Pattern Recognition — 111 citations into it; #4,515 of 21,575 by trust here, #1,816 by citations
- Evaluation & Benchmarks — 87 citations into it; #652 of 3,147 by trust here, #440 by citations
- Safety, Robustness & Interpretability — 44 citations into it; #1,491 of 2,251 by trust here, #889 by citations
- Large Language Models — 24 citations into it
- Representation & Self-Supervised Learning — 17 citations into it
- Generative Models — 11 citations into it
Whom Dheeru Dua trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Alex Krizhevsky
- Ilya Sutskever
- Yann LeCun
- Kaiming He
- Alex Graves
- Jacob Devlin
- Richard Socher
Who trusts Dheeru Dua overall
- Swaroop Mishra
- Matt Gardner
- Daniel Khashabi
- Tushar Khot
- Mor Geva
- Xi Ye
- Jonathan Berant
- Eric Wallace
- Alon Talmor
- Robin Jia
Papers from Dheeru Dua's perspective
Ordered by how strongly the researchers Dheeru Dua trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs (2019) — 1,328 citations
- Generating Natural Adversarial Examples (2017) — 659 citations
- Evaluating Models’ Local Decision Boundaries via Contrast Sets (2020) — 462 citations
- Evaluating NLP Models via Contrast Sets (2020) — 85 citations
- Tricks for Training Sparse Translation Models (2021) — 23 citations
- Benefits of Intermediate Annotations in Reading Comprehension (2020) — 34 citations
- Successive Prompting for Decomposing Complex Questions (2022) — 153 citations
- Comprehensive Multi-Dataset Evaluation of Reading Comprehension (2019) — 9 citations
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations