João Sedoc
Artificial Intelligence · with Ungar · 2018–2024
A researcher in the Science corpus: 10 papers; trusts 252 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 305 citations into it; #16,280 of 35,345 by trust here, #5,834 by citations
- Natural Language Processing — 273 citations into it; #4,052 of 5,688 by trust here, #1,504 by citations
- Evaluation & Benchmarks — 119 citations into it
- Computer Vision and Pattern Recognition — 78 citations into it
- Representation & Self-Supervised Learning — 41 citations into it; #2,629 of 3,145 by trust here, #2,910 by citations
- Safety, Robustness & Interpretability — 31 citations into it
- Cognitive Neuroscience — 11 citations into it
- General Social Sciences — 11 citations into it
Whom João Sedoc trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Herbert Jaeger
- Tomas Mikolov
- Diederik P. Kingma
- Geoffrey E. Hinton
- Ilya Sutskever
- Yoshua Bengio
- Dirk Hovy
- Richard Socher
- Alex Krizhevsky
- Yann LeCun
Who trusts João Sedoc overall
Papers from João Sedoc's perspective
Ordered by how strongly the researchers João Sedoc 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- 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
- 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)
- ImageNet: A large-scale hierarchical image database
Their papers
- The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics (2021) — 329 citations
- Comparison of Diverse Decoding Methods from Conditional Language Models (2019) — 135 citations
- GEMv2: Multilingual NLG Benchmarking in a Single Line of Code (2022) — 43 citations
- Modeling Empathy and Distress in Reaction to News Stories (2018) — 152 citations
- COD3S: Diverse Generation with Discrete Semantic Signatures (2020) — 15 citations
- The Role of Protected Class Word Lists in Bias Identification of Contextualized Word Representations (2019) — 21 citations
- Large language models could change the future of behavioral healthcare: a proposal for responsible development and evaluation (2024) — 308 citations
- Continual Learning for Sentence Representations Using Conceptors (2019) — 54 citations
- Conceptor Debiasing of Word Representations Evaluated on WEAT (2019) — 35 citations
- Unsupervised Post-processing of Word Vectors via Conceptor Negation (2018) — 22 citations