Manik Bhandari

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 56 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 75 citations into it; #16,251 of 35,345 by trust here, #13,163 by citations
• Natural Language Processing — 75 citations into it; #3,761 of 5,688 by trust here, #3,053 by citations
• Evaluation & Benchmarks — 33 citations into it; #1,835 of 3,147 by trust here, #2,040 by citations
• Computer Vision and Pattern Recognition — 17 citations into it; #19,099 of 21,575 by trust here, #15,955 by citations
• Model Architectures — 5 citations into it

Whom Manik Bhandari trusts overall

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

1. Chin-Yew Lin
2. Maxime Peyrard
3. Diederik P. Kingma
4. Christopher D. Manning
5. Yoshua Bengio
6. Yvette Graham
7. Geoffrey E. Hinton
8. Ani Nenkova
9. Ilya Sutskever
10. Ramesh Nallapati

Who trusts Manik Bhandari overall

1. Sebastian Gehrmann
2. Pierre Colombo
3. Daniel Deutsch
4. Shiyue Zhang
5. Mingqi Gao
6. Pengfei Liu
7. Elizabeth Clark
8. Weizhe Yuan
9. Yixin Liu
10. Thibault Sellam

Papers from Manik Bhandari's perspective

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

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

Their papers

• Submodular Optimization-based Diverse Paraphrasing and its Effectiveness in Data Augmentation (2019) — 128 citations
• Re-evaluating Evaluation in Text Summarization (2020) — 216 citations
• Metrics also Disagree in the Low Scoring Range: Revisiting Summarization Evaluation Metrics (2020) — 20 citations