Ananya B. Sai
Natural Language Processing · 2018–2021
A researcher in the Science corpus: 5 papers; trusts 391 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 244 citations into it; #5,469 of 5,688 by trust here, #2,808 by citations
- Artificial Intelligence — 233 citations into it; #21,556 of 35,345 by trust here, #11,490 by citations
- Evaluation & Benchmarks — 140 citations into it; #3,103 of 3,147 by trust here, #2,590 by citations
- Computer Vision and Pattern Recognition — 81 citations into it; #21,125 of 21,575 by trust here, #11,083 by citations
- Representation & Self-Supervised Learning — 20 citations into it
- Information Systems — 12 citations into it
- Model Architectures — 9 citations into it
- Multimodal Learning — 9 citations into it
Whom Ananya B. Sai trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Richard Socher
- Oriol Vinyals
- Chin-Yew Lin
- Yann LeCun
- Kaiming He
Who trusts Ananya B. Sai overall
- Sebastian Gehrmann
- Prakhar Gupta
- Akash Kumar Mohankumar
- Huihan Li
- Tanay Dixit
- Mitesh M. Khapra
- Zheng Ye
- Francesco Moramarco
- Nicholas Meade
- Dev Yashpal Sheth
Papers from Ananya B. Sai's perspective
Ordered by how strongly the researchers Ananya B. Sai trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- A Survey of Evaluation Metrics Used for NLG Systems (2020) — 344 citations
- ElimiNet: A Model for Eliminating Options for Reading Comprehension with Multiple Choice Questions (2018) — 31 citations
- NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation (2021) — 104 citations
- Improving Dialog Evaluation with a Multi-reference Adversarial Dataset and Large Scale Pretraining (2020) — 83 citations
- Perturbation CheckLists for Evaluating NLG Evaluation Metrics (2021) — 69 citations