Koustuv Sinha
Artificial Intelligence · 2017–2021
A researcher in the Science corpus: 8 papers; trusts 253 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 269 citations into it; #13,974 of 35,345 by trust here, #6,064 by citations
- Natural Language Processing — 234 citations into it; #2,611 of 5,688 by trust here, #1,626 by citations
- Evaluation & Benchmarks — 87 citations into it
- Computer Vision and Pattern Recognition — 73 citations into it
- Safety, Robustness & Interpretability — 43 citations into it
- Representation & Self-Supervised Learning — 31 citations into it
- Large Language Models — 28 citations into it
- Model Architectures — 23 citations into it
Whom Koustuv Sinha trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Diederik P. Kingma
- Alex Krizhevsky
- Tomas Mikolov
- Yann LeCun
- Oriol Vinyals
- Sepp Hochreiter
- Kaiming He
Who trusts Koustuv Sinha overall
- Ethan Perez
- Douwe Kiela
- Yifei Li
- Gregor Betz
- Albert Webson
- Kyle Richardson
- Prasanna Parthasarathi
- Adina Williams
- Ulme Wennberg
- Peter Clark
Papers from Koustuv Sinha's perspective
Ordered by how strongly the researchers Koustuv Sinha 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)
- ImageNet classification with deep convolutional neural networks
- 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
- 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
- Ethical Challenges in Data-Driven Dialogue Systems (2017) — 190 citations
- Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program) (2020) — 607 citations
- Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little (2021) — 297 citations
- UnNatural Language Inference (2020) — 102 citations
- CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text (2019) — 274 citations
- Evaluating Gender Bias in Natural Language Inference (2021) — 46 citations
- Sometimes We Want Ungrammatical Translations (2021) — 12 citations
- Learning an Unreferenced Metric for Online Dialogue Evaluation (2020) — 88 citations