Omri Abend

Artificial Intelligence · 2013–2024

A researcher in the Science corpus: 6 papers; trusts 119 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 145 citations into it; #18,920 of 35,345 by trust here, #15,004 by citations
• Natural Language Processing — 110 citations into it; #1,748 of 5,688 by trust here, #2,364 by citations
• Evaluation & Benchmarks — 44 citations into it; #2,085 of 3,147 by trust here, #2,166 by citations
• Computer Vision and Pattern Recognition — 43 citations into it
• Reinforcement Learning — 13 citations into it
• Developmental and Educational Psychology — 10 citations into it
• Linguistics — 7 citations into it

Whom Omri Abend trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Luke S. Zettlemoyer
2. Michael Collins
3. Noam Chomsky
4. Geoffrey E. Hinton
5. Sharon Goldwater
6. Matthew J. Beal
7. Yoshua Bengio
8. T. Griffiths
9. Brian MacWhinney
10. Diederik P. Kingma

Who trusts Omri Abend overall

1. Yanai Elazar
2. Aishwarya Kamath
3. Julian Michael
4. Yu Wang
5. Swabha Swayamdipta
6. Yoav Goldberg
7. Luheng He
8. Fernando Alva-Manchego
9. Luke S. Zettlemoyer
10. Rajarshi Das

Papers from Omri Abend's perspective

Ordered by how strongly the researchers Omri Abend trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. ImageNet classification with deep convolutional neural networks
6. Gradient-based learning applied to document recognition
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• BLEU is Not Suitable for the Evaluation of Text Simplification (2018) — 225 citations
• On the Weaknesses of Reinforcement Learning for Neural Machine Translation (2019) — 127 citations
• Bootstrapping language acquisition. (2017) — 90 citations
• Jamba: A Hybrid Transformer-Mamba Language Model (2024) — 467 citations
• Q^{2}: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering (2021) — 167 citations
• Universal Conceptual Cognitive Annotation (UCCA) (2013) — 233 citations