Bill Dolan
Artificial Intelligence · 2006–2022
A researcher in the Science corpus: 11 papers; trusts 170 researchers and is trusted by 35 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 214 citations into it; #9,204 of 35,345 by trust here, #3,598 by citations
- Natural Language Processing — 198 citations into it; #1,403 of 5,688 by trust here, #818 by citations
- Computer Vision and Pattern Recognition — 56 citations into it
- Evaluation & Benchmarks — 50 citations into it; #1,123 of 3,147 by trust here, #704 by citations
- Large Language Models — 40 citations into it
- Safety, Robustness & Interpretability — 23 citations into it
- Information Retrieval & Search — 14 citations into it
Whom Bill Dolan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Alec Radford
- Yann LeCun
- Oriol Vinyals
- Richard Socher
- Alex Graves
Who trusts Bill Dolan overall
- Ido Dagan
- Ivan Habernal
- Stefan Harmeling
- Li Dong
- Iris Hendrickx
- Bernardo Magnini
- Jonathan Berant
- Ion Androutsopoulos
- James Thorne
- Iryna Gurevych
Papers from Bill Dolan's perspective
Ordered by how strongly the researchers Bill Dolan trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- Long Short-Term Memory
- 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- What Makes Good In-Context Examples for GPT-3? (2021) — 1,798 citations
- The Third PASCAL Recognizing Textual Entailment Challenge (2007) — 290 citations
- Contextualized Perturbation for Textual Adversarial Attack (2020) — 285 citations
- Recognizing textual entailment: Rational, evaluation and approaches (2009) — 230 citations
- Text Editing by Command (2020) — 44 citations
- GODEL: Large-Scale Pre-Training for Goal-Directed Dialog (2022) — 80 citations
- Automatic Document Sketching: Generating Drafts from Analogous Texts (2021) — 7 citations
- A Controllable Model of Grounded Response Generation (2020) — 89 citations
- Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing (2007) — 81 citations
- Grounded Response Generation Task at DSTC7 (2019)
- The Second PASCAL Recognising Textual Entailment Challenge (2006)