Candace Ross

Artificial Intelligence · 2018–2022

A researcher in the Science corpus: 5 papers; trusts 352 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 218 citations into it
• Natural Language Processing — 161 citations into it
• Computer Vision and Pattern Recognition — 116 citations into it
• Safety, Robustness & Interpretability — 61 citations into it
• Multimodal Learning — 50 citations into it
• Evaluation & Benchmarks — 47 citations into it
• Large Language Models — 29 citations into it
• Representation & Self-Supervised Learning — 18 citations into it

Whom Candace Ross trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Kaiming He
5. Alex Krizhevsky
6. Ilya Sutskever
7. Yann LeCun
8. Ross B. Girshick
9. Alex Graves
10. Jimmy Ba

Who trusts Candace Ross overall

1. Jaemin Cho
2. Eric Michael Smith
3. Sanjay Subramanian
4. Jing Yu Koh
5. Saghar Hosseini
6. Armen Aghajanyan

Papers from Candace Ross's perspective

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

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

Their papers

• CM3: A Causal Masked Multimodal Model of the Internet (2022) — 180 citations
• Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality (2022) — 639 citations
• Grounding language acquisition by training semantic parsers using captioned videos (2018) — 17 citations
• Measuring Social Biases in Grounded Vision and Language Embeddings (2020) — 73 citations
• Perturbation Augmentation for Fairer NLP (2022) — 73 citations