Vishwajeet Kumar

Artificial Intelligence · 2018–2026

A researcher in the Science corpus: 7 papers; trusts 103 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 146 citations into it; #25,598 of 35,345 by trust here, #26,682 by citations
• Natural Language Processing — 99 citations into it; #2,639 of 5,688 by trust here, #4,250 by citations
• Computer Vision and Pattern Recognition — 44 citations into it; #15,692 of 21,575 by trust here, #17,258 by citations
• Evaluation & Benchmarks — 33 citations into it
• Information Systems — 17 citations into it
• Model Architectures — 13 citations into it
• Reinforcement Learning — 7 citations into it; #1,536 of 2,242 by trust here, #2,160 by citations
• Management Science and Operations Research — 5 citations into it

Whom Vishwajeet Kumar trusts overall

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

1. Diederik P. Kingma
2. Oriol Vinyals
3. Dzmitry Bahdanau
4. Justus J. Randolph
5. Yoshua Bengio
6. Geoffrey E. Hinton
7. Chin-Yew Lin
8. Kyunghyun Cho
9. Xinya Du
10. Ilya Sutskever

Who trusts Vishwajeet Kumar overall

1. Shiyue Zhang
2. Mohit Bansal
3. Tom Hosking
4. Duo Chai
5. Nitish Joshi
6. Ganesh Ramakrishnan
7. Sebastian Riedel
8. Zewen Chi
9. Arijit Mukherjee
10. Priyanka Agrawal

Papers from Vishwajeet Kumar's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Cross-Lingual Training for Automatic Question Generation (2019) — 61 citations
• Putting the Horse before the Cart: A Generator-Evaluator Framework for Question Generation from Text (2018) — 44 citations
• Granite Embedding Multilingual R2 Models (2026)
• Granite Embedding R2 Models (2025)
• Granite Embedding Models (2025)
• A Weakly Supervised Model for Solving Math word Problems (2021) — 6 citations
• A framework for automatic question generation from text using deep reinforcement learning (2018) — 47 citations