Hila Gonen
Artificial Intelligence · 2019–2022
A researcher in the Science corpus: 7 papers; trusts 92 researchers and is trusted by 105 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 92 citations into it; #2,841 of 35,345 by trust here, #4,137 by citations
- Natural Language Processing — 58 citations into it; #717 of 5,688 by trust here, #1,050 by citations
- Safety, Robustness & Interpretability — 37 citations into it; #151 of 2,251 by trust here, #281 by citations
- Representation & Self-Supervised Learning — 33 citations into it
- Computer Vision and Pattern Recognition — 15 citations into it; #4,019 of 21,575 by trust here, #4,525 by citations
- Safety Research — 10 citations into it
- Evaluation & Benchmarks — 8 citations into it
- Cognitive Neuroscience — 7 citations into it
Whom Hila Gonen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tomas Mikolov
- Geoffrey E. Hinton
- L. V. D. van der Maaten
- Jeffrey Pennington
- Yoshua Bengio
- Aylin Caliskan
- Richard Socher
- Tolga Bolukbasi
- Jieyu Zhao
- Diederik P. Kingma
Who trusts Hila Gonen overall
- Shikha Bordia
- Anne Lauscher
- Sunipa Dev
- Marta Ruiz Costa-jussà
- Thomas Hellström
- Samuel R. Bowman
- Dirk Hovy
- Adina Williams
- Emily Dinan
- Adithya Renduchintala
Papers from Hila Gonen's perspective
Ordered by how strongly the researchers Hila Gonen 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
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them (2019) — 632 citations
- Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection (2020) — 555 citations
- It’s All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitution (2019) — 202 citations
- Automatically Identifying Gender Issues in Machine Translation using Perturbations (2020) — 46 citations
- Demystifying Prompts in Language Models via Perplexity Estimation (2022) — 313 citations
- Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them (2019) — 47 citations
- How does Grammatical Gender Affect Noun Representations in Gender-Marking Languages? (2019) — 26 citations