Saad Mahamood
Artificial Intelligence · 2015–2022
A researcher in the Science corpus: 7 papers; trusts 18 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 279 citations into it; #15,443 of 35,345 by trust here, #6,468 by citations
- Natural Language Processing — 263 citations into it; #2,616 of 5,688 by trust here, #1,305 by citations
- Evaluation & Benchmarks — 154 citations into it; #1,500 of 3,147 by trust here, #899 by citations
- Information Systems — 26 citations into it
- Molecular Biology — 7 citations into it
- Linguistics — 6 citations into it
Whom Saad Mahamood trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ehud Reiter
- Anya Belz
- Chin-Yew Lin
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Mihir Kale
- Tal Linzen
- Xiaofei Lu
Who trusts Saad Mahamood overall
Papers from Saad Mahamood's perspective
Ordered by how strongly the researchers Saad Mahamood trusts endorse each paper. Same corpus, a different order for every researcher.
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Attention is All you Need (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Language Models are Unsupervised Multitask Learners
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Bleu: a Method for Automatic Evaluation of Machine Translation
Their papers
- The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics (2021) — 329 citations
- Automatic Construction of Evaluation Suites for Natural Language Generation Datasets (2021) — 27 citations
- GEMv2: Multilingual NLG Benchmarking in a Single Line of Code (2022) — 43 citations
- A Snapshot of NLG Evaluation Practices 2005 - 2014 (2015) — 58 citations
- NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation (2021) — 104 citations
- Underreporting of errors in NLG output, and what to do about it (2021) — 42 citations
- Twenty Years of Confusion in Human Evaluation: NLG Needs Evaluation Sheets and Standardised Definitions (2020) — 263 citations