Nithum Thain
Artificial Intelligence · 2016–2024
A researcher in the Science corpus: 9 papers; trusts 36 researchers and is trusted by 118 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 146 citations into it; #2,148 of 35,345 by trust here, #2,278 by citations
- Natural Language Processing — 65 citations into it; #1,772 of 5,688 by trust here, #1,229 by citations
- Safety, Robustness & Interpretability — 53 citations into it; #186 of 2,251 by trust here, #262 by citations
- Safety Research — 36 citations into it; #2,366 of 5,829 by trust here, #806 by citations
- Evaluation & Benchmarks — 24 citations into it; #2,135 of 3,147 by trust here, #1,467 by citations
- Information Systems — 21 citations into it; #496 of 8,771 by trust here, #707 by citations
- Communication — 13 citations into it; #113 of 3,460 by trust here, #263 by citations
- Representation & Self-Supervised Learning — 11 citations into it
Whom Nithum Thain trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Moritz Hardt
- Charu C. Aggarwal
- Yoshua Bengio
- James Bergstra
- Diederik P. Kingma
- Geoffrey E. Hinton
- Jeffrey Pennington
- Richard Socher
- Alex Krizhevsky
- Alex Beutel
Who trusts Nithum Thain overall
- Svetlana Kiritchenko
- Isar Nejadgholi
- Oguzhan Gencoglu
- John Pavlopoulos
- Mladen Karan
- Jing Xu
- Maarten Sap
- Bertie Vidgen
- Yi Tay
- Emily Dinan
Papers from Nithum Thain's perspective
Ordered by how strongly the researchers Nithum Thain 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)
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- GENERATIVE ADVERSARIAL NETS
Their papers
- Measuring and Mitigating Unintended Bias in Text Classification (2018) — 916 citations
- Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification (2019) — 607 citations
- Ex Machina: Personal Attacks Seen at Scale (2016) — 846 citations
- Fairness without Demographics through Adversarially Reweighted Learning (2020) — 399 citations
- Conversations Gone Awry: Detecting Early Signs of Conversational Failure (2018) — 223 citations
- Debiasing Embeddings for Reduced Gender Bias in Text Classification (2019) — 53 citations
- Gemma: Open Models Based on Gemini Research and Technology (2024) — 1,150 citations
- Towards Agile Text Classifiers for Everyone (2023) — 14 citations
- Crowdsourcing Subjective Tasks: The Case Study of Understanding Toxicity in Online Discussions (2019) — 85 citations