Aaron Gokaslan
Artificial Intelligence · with Nguyen · 2022–2024
A researcher in the Science corpus: 5 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 261 citations into it
- Natural Language Processing — 171 citations into it
Whom Aaron Gokaslan trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio (in Artificial Intelligence)
- Christopher D. Manning (in Artificial Intelligence)
- Diederik P. Kingma (in Artificial Intelligence)
- Quoc V. Le (in Artificial Intelligence)
- Kenton C. T. Lee (in Artificial Intelligence)
- Ilya Sutskever (in Artificial Intelligence)
- Jimmy Ba (in Artificial Intelligence)
- Geoffrey E. Hinton (in Artificial Intelligence)
- Luke S. Zettlemoyer (in Artificial Intelligence)
- Samuel R. Bowman (in Artificial Intelligence)
Papers from Aaron Gokaslan's perspective
Ordered by how strongly the researchers Aaron Gokaslan trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
- Language Models are Unsupervised Multitask Learners
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
- Improving Language Understanding by Generative Pre-Training
- 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)
Their papers
- Data Governance in the Age of Large-Scale Data-Driven Language Technology (2022) — 65 citations
- The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset (2023) — 217 citations
- DataComp-LM: In search of the next generation of training sets for language models (2024) — 374 citations
- Emergent Structures and Training Dynamics in Large Language Models (2022)
- BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022) — 2,975 citations