Elena L. Glassman
Artificial Intelligence · 2014–2022
A researcher in the Science corpus: 5 papers; trusts 13 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 46 citations into it
- Information Systems — 22 citations into it; #7,782 of 8,771 by trust here, #2,741 by citations
- Natural Language Processing — 19 citations into it
- Human-Computer Interaction — 14 citations into it; #1,695 of 2,253 by trust here, #468 by citations
- Safety, Robustness & Interpretability — 13 citations into it
- Software — 13 citations into it; #1,082 of 1,227 by trust here, #839 by citations
- Safety Research — 9 citations into it
- Management Science and Operations Research — 5 citations into it
Whom Elena L. Glassman trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- F. Marton
- Saul Schleimer
- Thomas Hofmann
- Stephen Slade
- Himabindu Lakkaraju
- David M. Blei
- Agnar Aamodt
- Been Kim
- Daniel Shawcross Wilkerson
- Michael I. Jordan
Who trusts Elena L. Glassman overall
- Been Kim
- Shraddha Barke
- Rahul Gupta
- Michael B. James
- Marco Tulio Ribeiro
- Aditya Kanade
- Ashraf Abdul
- Menaka Narayanan
Papers from Elena L. Glassman's perspective
Ordered by how strongly the researchers Elena L. Glassman trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Expectation vs. Experience: Evaluating the Usability of Code Generation Tools Powered by Large Language Models (2022) — 744 citations
- Proxy tasks and subjective measures can be misleading in evaluating explainable AI systems (2020) — 379 citations
- OverCode (2015) — 92 citations
- iBCM: Interactive Bayesian Case Model Empowering Humans via Intuitive Interaction (2015) — 55 citations
- OverCode: visualizing variation in student solutions to programming problems at scale (2014) — 199 citations