Rotem Dror
Artificial Intelligence · 2018–2023
A researcher in the Science corpus: 5 papers; trusts 46 researchers and is trusted by 17 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 82 citations into it; #10,127 of 35,345 by trust here, #11,072 by citations
- Natural Language Processing — 61 citations into it; #2,375 of 5,688 by trust here, #2,930 by citations
- Evaluation & Benchmarks — 52 citations into it; #1,036 of 3,147 by trust here, #1,517 by citations
- Statistics and Probability — 29 citations into it
- Computer Vision and Pattern Recognition — 14 citations into it
- Molecular Biology — 5 citations into it
Whom Rotem Dror trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Chin-Yew Lin
- Alexander S. Yeh
- Philipp Koehn
- K. Erk
- Yvette Graham
- Yftah Ziser
- John Blitzer
- Daniel Deutsch
- Michael Collins
- Geoffrey E. Hinton
Who trusts Rotem Dror overall
- Steven Bethard
- Zhiruo Wang
- Johnny Tian-Zheng Wei
- Guy Rotman
- David M. Howcroft
- Ryan T. McDonald
- Daniel Deutsch
- Rongzhi Zhang
- Markus Freitag
- Graham Neubig
Papers from Rotem Dror's perspective
Ordered by how strongly the researchers Rotem Dror 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)
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- 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
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
Their papers
- The Hitchhiker’s Guide to Testing Statistical Significance in Natural Language Processing (2018) — 487 citations
- A Statistical Analysis of Summarization Evaluation Metrics Using Resampling Methods (2021) — 96 citations
- Re-Examining System-Level Correlations of Automatic Summarization Evaluation Metrics (2022) — 53 citations
- State of What Art? A Call for Multi-Prompt LLM Evaluation (2023) — 343 citations
- Statistical Significance Testing for Natural Language Processing (2020) — 54 citations