Sunipa Dev
Artificial Intelligence · 2019–2023
A researcher in the Science corpus: 12 papers; trusts 358 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 556 citations into it; #6,440 of 35,345 by trust here, #1,000 by citations
- Natural Language Processing — 385 citations into it; #4,458 of 5,688 by trust here, #2,106 by citations
- Safety, Robustness & Interpretability — 273 citations into it; #1,952 of 2,251 by trust here, #816 by citations
- Evaluation & Benchmarks — 115 citations into it
- Computer Vision and Pattern Recognition — 111 citations into it
- Large Language Models — 79 citations into it
- Representation & Self-Supervised Learning — 54 citations into it; #965 of 3,145 by trust here, #2,120 by citations
- Safety Research — 49 citations into it
Whom Sunipa Dev trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tomas Mikolov
- Omer Levy
- Ilya Sutskever
- Geoffrey E. Hinton
- Yoshua Bengio
- Richard Socher
- Jacob Devlin
- Diederik P. Kingma
- Christopher D. Manning
- Aylin Caliskan
Who trusts Sunipa Dev overall
- Tao Li
- Anne Lauscher
- Oskar van der Wal
- Yusuke Hirota
- Gauri Gupta
- Radovan Popović
- Jeff M. Phillips
- Enoch Opanin Gyamfi
- Vivek Srikumar
- Daniel Khashabi
Papers from Sunipa Dev's perspective
Ordered by how strongly the researchers Sunipa Dev trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- 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
- PaLM: Scaling Language Modeling with Pathways (2022) — 8,214 citations
- PaLM 2 Technical Report (2023) — 1,524 citations
- Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies (2021) — 214 citations
- Re-contextualizing Fairness in NLP: The Case of India (2022) — 84 citations
- On Measuring and Mitigating Biased Inferences of Word Embeddings (2019) — 198 citations
- Attenuating Bias in Word Vectors (2019) — 161 citations
- OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings (2020) — 60 citations
- On Measures of Biases and Harms in NLP (2021) — 126 citations
- The Tail Wagging the Dog: Dataset Construction Biases of Social Bias Benchmarks (2022) — 34 citations
- Socially Aware Bias Measurements for Hindi Language Representations (2021) — 50 citations
- What do Bias Measures Measure? (2021) — 15 citations
- The Geometry of Distributed Representations for Better Alignment, Attenuated Bias, and Improved Interpretability (2020)