Rangan Majumder
Artificial Intelligence · 2016–2024
A researcher in the Science corpus: 6 papers; trusts 47 researchers and is trusted by 22 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 164 citations into it; #25,602 of 35,345 by trust here, #3,937 by citations
- Natural Language Processing — 122 citations into it
- Computer Vision and Pattern Recognition — 68 citations into it
- Evaluation & Benchmarks — 46 citations into it; #841 of 3,147 by trust here, #187 by citations
- Representation & Self-Supervised Learning — 37 citations into it
Whom Rangan Majumder trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ilya Sutskever
- Geoffrey E. Hinton
- Yoshua Bengio
- Kaiming He
- Sepp Hochreiter
- Diederik P. Kingma
- Alex Krizhevsky
- Yann LeCun
- J. Urgen Schmidhuber
- Oriol Vinyals
Who trusts Rangan Majumder overall
- Sebastian Hofstätter
- Hong-Liu Cao
- Jimmy J. Lin
- Luyu Gao
- Omar Khattab
- Luke Merrick
- Rodrigo Nogueira
- Zhuyun Dai
- Bhaskar Mitra
Papers from Rangan Majumder's perspective
Ordered by how strongly the researchers Rangan Majumder 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
Their papers
- XGLUE: A New Benchmark Datasetfor Cross-lingual Pre-training, Understanding and Generation (2020) — 398 citations
- Text Embeddings by Weakly-Supervised Contrastive Pre-training (2022) — 1,460 citations
- Multilingual E5 Text Embeddings: A Technical Report (2024) — 521 citations
- Improving Text Embeddings with Large Language Models (2023) — 400 citations
- MS MARCO: A Human Generated MAchine Reading COmprehension Dataset (2016) — 524 citations
- MS MARCO: A Human Generated MAchine Reading COmprehension Dataset (2016) — 3,491 citations